1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc/private/vecimpl.h> 4 #include <petsc/private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 12 and MATMPIAIJ otherwise. As a result, for single process communicators, 13 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 19 20 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 21 enough exist. 22 23 Level: beginner 24 25 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 26 M*/ 27 28 /*MC 29 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 30 31 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 32 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 33 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 34 for communicators controlling multiple processes. It is recommended that you call both of 35 the above preallocation routines for simplicity. 36 37 Options Database Keys: 38 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 39 40 Level: beginner 41 42 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 43 M*/ 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 47 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 48 { 49 PetscErrorCode ierr; 50 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 52 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 53 const PetscInt *ia,*ib; 54 const MatScalar *aa,*bb; 55 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 56 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 57 58 PetscFunctionBegin; 59 *keptrows = 0; 60 ia = a->i; 61 ib = b->i; 62 for (i=0; i<m; i++) { 63 na = ia[i+1] - ia[i]; 64 nb = ib[i+1] - ib[i]; 65 if (!na && !nb) { 66 cnt++; 67 goto ok1; 68 } 69 aa = a->a + ia[i]; 70 for (j=0; j<na; j++) { 71 if (aa[j] != 0.0) goto ok1; 72 } 73 bb = b->a + ib[i]; 74 for (j=0; j <nb; j++) { 75 if (bb[j] != 0.0) goto ok1; 76 } 77 cnt++; 78 ok1:; 79 } 80 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 81 if (!n0rows) PetscFunctionReturn(0); 82 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 83 cnt = 0; 84 for (i=0; i<m; i++) { 85 na = ia[i+1] - ia[i]; 86 nb = ib[i+1] - ib[i]; 87 if (!na && !nb) continue; 88 aa = a->a + ia[i]; 89 for (j=0; j<na;j++) { 90 if (aa[j] != 0.0) { 91 rows[cnt++] = rstart + i; 92 goto ok2; 93 } 94 } 95 bb = b->a + ib[i]; 96 for (j=0; j<nb; j++) { 97 if (bb[j] != 0.0) { 98 rows[cnt++] = rstart + i; 99 goto ok2; 100 } 101 } 102 ok2:; 103 } 104 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 105 PetscFunctionReturn(0); 106 } 107 108 #undef __FUNCT__ 109 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 110 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 111 { 112 PetscErrorCode ierr; 113 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 114 115 PetscFunctionBegin; 116 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 117 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 118 } else { 119 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 120 } 121 PetscFunctionReturn(0); 122 } 123 124 125 #undef __FUNCT__ 126 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 127 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 128 { 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 130 PetscErrorCode ierr; 131 PetscInt i,rstart,nrows,*rows; 132 133 PetscFunctionBegin; 134 *zrows = NULL; 135 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 136 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 137 for (i=0; i<nrows; i++) rows[i] += rstart; 138 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 #undef __FUNCT__ 143 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 144 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 145 { 146 PetscErrorCode ierr; 147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 148 PetscInt i,n,*garray = aij->garray; 149 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 150 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 151 PetscReal *work; 152 153 PetscFunctionBegin; 154 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 155 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 156 if (type == NORM_2) { 157 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 158 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 159 } 160 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 161 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 162 } 163 } else if (type == NORM_1) { 164 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 165 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 166 } 167 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 168 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 169 } 170 } else if (type == NORM_INFINITY) { 171 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 172 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 173 } 174 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 175 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 176 } 177 178 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 179 if (type == NORM_INFINITY) { 180 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 181 } else { 182 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 183 } 184 ierr = PetscFree(work);CHKERRQ(ierr); 185 if (type == NORM_2) { 186 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 187 } 188 PetscFunctionReturn(0); 189 } 190 191 #undef __FUNCT__ 192 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_MPIAIJ" 193 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 194 { 195 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 196 IS sis,gis; 197 PetscErrorCode ierr; 198 const PetscInt *isis,*igis; 199 PetscInt n,*iis,nsis,ngis,rstart,i; 200 201 PetscFunctionBegin; 202 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 203 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 204 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 205 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 206 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 207 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 208 209 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 210 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 211 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 212 n = ngis + nsis; 213 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 214 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 215 for (i=0; i<n; i++) iis[i] += rstart; 216 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 217 218 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 219 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 220 ierr = ISDestroy(&sis);CHKERRQ(ierr); 221 ierr = ISDestroy(&gis);CHKERRQ(ierr); 222 PetscFunctionReturn(0); 223 } 224 225 #undef __FUNCT__ 226 #define __FUNCT__ "MatDistribute_MPIAIJ" 227 /* 228 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 229 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 230 231 Only for square matrices 232 233 Used by a preconditioner, hence PETSC_EXTERN 234 */ 235 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 236 { 237 PetscMPIInt rank,size; 238 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 239 PetscErrorCode ierr; 240 Mat mat; 241 Mat_SeqAIJ *gmata; 242 PetscMPIInt tag; 243 MPI_Status status; 244 PetscBool aij; 245 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 246 247 PetscFunctionBegin; 248 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 249 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 250 if (!rank) { 251 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 252 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 253 } 254 if (reuse == MAT_INITIAL_MATRIX) { 255 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 256 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 257 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 258 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 259 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 260 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 261 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 262 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 263 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 264 265 rowners[0] = 0; 266 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 267 rstart = rowners[rank]; 268 rend = rowners[rank+1]; 269 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 270 if (!rank) { 271 gmata = (Mat_SeqAIJ*) gmat->data; 272 /* send row lengths to all processors */ 273 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 274 for (i=1; i<size; i++) { 275 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 276 } 277 /* determine number diagonal and off-diagonal counts */ 278 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 279 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 280 jj = 0; 281 for (i=0; i<m; i++) { 282 for (j=0; j<dlens[i]; j++) { 283 if (gmata->j[jj] < rstart) ld[i]++; 284 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 285 jj++; 286 } 287 } 288 /* send column indices to other processes */ 289 for (i=1; i<size; i++) { 290 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 291 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 292 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 } 294 295 /* send numerical values to other processes */ 296 for (i=1; i<size; i++) { 297 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 298 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 299 } 300 gmataa = gmata->a; 301 gmataj = gmata->j; 302 303 } else { 304 /* receive row lengths */ 305 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 306 /* receive column indices */ 307 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 309 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 /* determine number diagonal and off-diagonal counts */ 311 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 312 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 313 jj = 0; 314 for (i=0; i<m; i++) { 315 for (j=0; j<dlens[i]; j++) { 316 if (gmataj[jj] < rstart) ld[i]++; 317 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 318 jj++; 319 } 320 } 321 /* receive numerical values */ 322 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* set preallocation */ 326 for (i=0; i<m; i++) { 327 dlens[i] -= olens[i]; 328 } 329 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 330 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 331 332 for (i=0; i<m; i++) { 333 dlens[i] += olens[i]; 334 } 335 cnt = 0; 336 for (i=0; i<m; i++) { 337 row = rstart + i; 338 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 339 cnt += dlens[i]; 340 } 341 if (rank) { 342 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 343 } 344 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 345 ierr = PetscFree(rowners);CHKERRQ(ierr); 346 347 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 348 349 *inmat = mat; 350 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 351 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 352 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 353 mat = *inmat; 354 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 355 if (!rank) { 356 /* send numerical values to other processes */ 357 gmata = (Mat_SeqAIJ*) gmat->data; 358 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 359 gmataa = gmata->a; 360 for (i=1; i<size; i++) { 361 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 362 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 363 } 364 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 365 } else { 366 /* receive numerical values from process 0*/ 367 nz = Ad->nz + Ao->nz; 368 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 369 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 370 } 371 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 372 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 373 ad = Ad->a; 374 ao = Ao->a; 375 if (mat->rmap->n) { 376 i = 0; 377 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 378 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 379 } 380 for (i=1; i<mat->rmap->n; i++) { 381 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 382 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 383 } 384 i--; 385 if (mat->rmap->n) { 386 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 387 } 388 if (rank) { 389 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 390 } 391 } 392 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 393 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 /* 398 Local utility routine that creates a mapping from the global column 399 number to the local number in the off-diagonal part of the local 400 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 401 a slightly higher hash table cost; without it it is not scalable (each processor 402 has an order N integer array but is fast to acess. 403 */ 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 #undef __FUNCT__ 499 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 500 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 501 { 502 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 504 PetscErrorCode ierr; 505 PetscInt l,*garray = mat->garray,diag; 506 507 PetscFunctionBegin; 508 /* code only works for square matrices A */ 509 510 /* find size of row to the left of the diagonal part */ 511 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 512 row = row - diag; 513 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 514 if (garray[b->j[b->i[row]+l]] > diag) break; 515 } 516 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 517 518 /* diagonal part */ 519 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 520 521 /* right of diagonal part */ 522 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 523 PetscFunctionReturn(0); 524 } 525 526 #undef __FUNCT__ 527 #define __FUNCT__ "MatSetValues_MPIAIJ" 528 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 529 { 530 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 531 PetscScalar value; 532 PetscErrorCode ierr; 533 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 534 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 535 PetscBool roworiented = aij->roworiented; 536 537 /* Some Variables required in the macro */ 538 Mat A = aij->A; 539 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 540 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 541 MatScalar *aa = a->a; 542 PetscBool ignorezeroentries = a->ignorezeroentries; 543 Mat B = aij->B; 544 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 545 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 546 MatScalar *ba = b->a; 547 548 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 549 PetscInt nonew; 550 MatScalar *ap1,*ap2; 551 552 PetscFunctionBegin; 553 for (i=0; i<m; i++) { 554 if (im[i] < 0) continue; 555 #if defined(PETSC_USE_DEBUG) 556 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 557 #endif 558 if (im[i] >= rstart && im[i] < rend) { 559 row = im[i] - rstart; 560 lastcol1 = -1; 561 rp1 = aj + ai[row]; 562 ap1 = aa + ai[row]; 563 rmax1 = aimax[row]; 564 nrow1 = ailen[row]; 565 low1 = 0; 566 high1 = nrow1; 567 lastcol2 = -1; 568 rp2 = bj + bi[row]; 569 ap2 = ba + bi[row]; 570 rmax2 = bimax[row]; 571 nrow2 = bilen[row]; 572 low2 = 0; 573 high2 = nrow2; 574 575 for (j=0; j<n; j++) { 576 if (roworiented) value = v[i*n+j]; 577 else value = v[i+j*m]; 578 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 579 if (in[j] >= cstart && in[j] < cend) { 580 col = in[j] - cstart; 581 nonew = a->nonew; 582 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 583 } else if (in[j] < 0) continue; 584 #if defined(PETSC_USE_DEBUG) 585 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 586 #endif 587 else { 588 if (mat->was_assembled) { 589 if (!aij->colmap) { 590 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 591 } 592 #if defined(PETSC_USE_CTABLE) 593 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 594 col--; 595 #else 596 col = aij->colmap[in[j]] - 1; 597 #endif 598 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 599 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 600 col = in[j]; 601 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 602 B = aij->B; 603 b = (Mat_SeqAIJ*)B->data; 604 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 605 rp2 = bj + bi[row]; 606 ap2 = ba + bi[row]; 607 rmax2 = bimax[row]; 608 nrow2 = bilen[row]; 609 low2 = 0; 610 high2 = nrow2; 611 bm = aij->B->rmap->n; 612 ba = b->a; 613 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 614 } else col = in[j]; 615 nonew = b->nonew; 616 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 617 } 618 } 619 } else { 620 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 621 if (!aij->donotstash) { 622 mat->assembled = PETSC_FALSE; 623 if (roworiented) { 624 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 625 } else { 626 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 627 } 628 } 629 } 630 } 631 PetscFunctionReturn(0); 632 } 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatGetValues_MPIAIJ" 636 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 641 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 642 643 PetscFunctionBegin; 644 for (i=0; i<m; i++) { 645 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 646 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 647 if (idxm[i] >= rstart && idxm[i] < rend) { 648 row = idxm[i] - rstart; 649 for (j=0; j<n; j++) { 650 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 651 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 652 if (idxn[j] >= cstart && idxn[j] < cend) { 653 col = idxn[j] - cstart; 654 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 655 } else { 656 if (!aij->colmap) { 657 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 658 } 659 #if defined(PETSC_USE_CTABLE) 660 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 661 col--; 662 #else 663 col = aij->colmap[idxn[j]] - 1; 664 #endif 665 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 666 else { 667 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 668 } 669 } 670 } 671 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 672 } 673 PetscFunctionReturn(0); 674 } 675 676 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 677 678 #undef __FUNCT__ 679 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 680 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 681 { 682 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 683 PetscErrorCode ierr; 684 PetscInt nstash,reallocs; 685 686 PetscFunctionBegin; 687 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 688 689 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 690 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 691 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 692 PetscFunctionReturn(0); 693 } 694 695 #undef __FUNCT__ 696 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 697 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 698 { 699 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 700 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 701 PetscErrorCode ierr; 702 PetscMPIInt n; 703 PetscInt i,j,rstart,ncols,flg; 704 PetscInt *row,*col; 705 PetscBool other_disassembled; 706 PetscScalar *val; 707 708 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 709 710 PetscFunctionBegin; 711 if (!aij->donotstash && !mat->nooffprocentries) { 712 while (1) { 713 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 714 if (!flg) break; 715 716 for (i=0; i<n; ) { 717 /* Now identify the consecutive vals belonging to the same row */ 718 for (j=i,rstart=row[j]; j<n; j++) { 719 if (row[j] != rstart) break; 720 } 721 if (j < n) ncols = j-i; 722 else ncols = n-i; 723 /* Now assemble all these values with a single function call */ 724 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 725 726 i = j; 727 } 728 } 729 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 730 } 731 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 732 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 733 734 /* determine if any processor has disassembled, if so we must 735 also disassemble ourselfs, in order that we may reassemble. */ 736 /* 737 if nonzero structure of submatrix B cannot change then we know that 738 no processor disassembled thus we can skip this stuff 739 */ 740 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 741 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 742 if (mat->was_assembled && !other_disassembled) { 743 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 744 } 745 } 746 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 747 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 748 } 749 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 750 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 751 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 752 753 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 754 755 aij->rowvalues = 0; 756 757 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 758 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 759 760 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 761 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 762 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 763 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 764 } 765 PetscFunctionReturn(0); 766 } 767 768 #undef __FUNCT__ 769 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 770 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 771 { 772 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 773 PetscErrorCode ierr; 774 775 PetscFunctionBegin; 776 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 777 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 778 PetscFunctionReturn(0); 779 } 780 781 #undef __FUNCT__ 782 #define __FUNCT__ "MatZeroRows_MPIAIJ" 783 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 784 { 785 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 786 PetscInt *owners = A->rmap->range; 787 PetscInt n = A->rmap->n; 788 PetscSF sf; 789 PetscInt *lrows; 790 PetscSFNode *rrows; 791 PetscInt r, p = 0, len = 0; 792 PetscErrorCode ierr; 793 794 PetscFunctionBegin; 795 /* Create SF where leaves are input rows and roots are owned rows */ 796 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 797 for (r = 0; r < n; ++r) lrows[r] = -1; 798 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 799 for (r = 0; r < N; ++r) { 800 const PetscInt idx = rows[r]; 801 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 802 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 803 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 804 } 805 if (A->nooffproczerorows) { 806 if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank); 807 lrows[len++] = idx - owners[p]; 808 } else { 809 rrows[r].rank = p; 810 rrows[r].index = rows[r] - owners[p]; 811 } 812 } 813 if (!A->nooffproczerorows) { 814 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 815 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 816 /* Collect flags for rows to be zeroed */ 817 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 818 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 819 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 820 /* Compress and put in row numbers */ 821 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 822 } 823 /* fix right hand side if needed */ 824 if (x && b) { 825 const PetscScalar *xx; 826 PetscScalar *bb; 827 828 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 829 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 830 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 831 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 832 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 833 } 834 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 835 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 836 if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) { 837 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 838 } else if (diag != 0.0) { 839 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 840 if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 841 for (r = 0; r < len; ++r) { 842 const PetscInt row = lrows[r] + A->rmap->rstart; 843 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 844 } 845 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 846 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 847 } else { 848 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 849 } 850 ierr = PetscFree(lrows);CHKERRQ(ierr); 851 852 /* only change matrix nonzero state if pattern was allowed to be changed */ 853 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 854 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 855 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 856 } 857 PetscFunctionReturn(0); 858 } 859 860 #undef __FUNCT__ 861 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 862 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 863 { 864 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 865 PetscErrorCode ierr; 866 PetscMPIInt n = A->rmap->n; 867 PetscInt i,j,r,m,p = 0,len = 0; 868 PetscInt *lrows,*owners = A->rmap->range; 869 PetscSFNode *rrows; 870 PetscSF sf; 871 const PetscScalar *xx; 872 PetscScalar *bb,*mask; 873 Vec xmask,lmask; 874 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 875 const PetscInt *aj, *ii,*ridx; 876 PetscScalar *aa; 877 878 PetscFunctionBegin; 879 /* Create SF where leaves are input rows and roots are owned rows */ 880 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 881 for (r = 0; r < n; ++r) lrows[r] = -1; 882 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 883 for (r = 0; r < N; ++r) { 884 const PetscInt idx = rows[r]; 885 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 886 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 887 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 888 } 889 rrows[r].rank = p; 890 rrows[r].index = rows[r] - owners[p]; 891 } 892 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 893 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 894 /* Collect flags for rows to be zeroed */ 895 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 896 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 897 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 898 /* Compress and put in row numbers */ 899 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 900 /* zero diagonal part of matrix */ 901 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 902 /* handle off diagonal part of matrix */ 903 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 904 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 905 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 906 for (i=0; i<len; i++) bb[lrows[i]] = 1; 907 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 908 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 909 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 910 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 911 if (x) { 912 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 913 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 914 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 915 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 916 } 917 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 918 /* remove zeroed rows of off diagonal matrix */ 919 ii = aij->i; 920 for (i=0; i<len; i++) { 921 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 922 } 923 /* loop over all elements of off process part of matrix zeroing removed columns*/ 924 if (aij->compressedrow.use) { 925 m = aij->compressedrow.nrows; 926 ii = aij->compressedrow.i; 927 ridx = aij->compressedrow.rindex; 928 for (i=0; i<m; i++) { 929 n = ii[i+1] - ii[i]; 930 aj = aij->j + ii[i]; 931 aa = aij->a + ii[i]; 932 933 for (j=0; j<n; j++) { 934 if (PetscAbsScalar(mask[*aj])) { 935 if (b) bb[*ridx] -= *aa*xx[*aj]; 936 *aa = 0.0; 937 } 938 aa++; 939 aj++; 940 } 941 ridx++; 942 } 943 } else { /* do not use compressed row format */ 944 m = l->B->rmap->n; 945 for (i=0; i<m; i++) { 946 n = ii[i+1] - ii[i]; 947 aj = aij->j + ii[i]; 948 aa = aij->a + ii[i]; 949 for (j=0; j<n; j++) { 950 if (PetscAbsScalar(mask[*aj])) { 951 if (b) bb[i] -= *aa*xx[*aj]; 952 *aa = 0.0; 953 } 954 aa++; 955 aj++; 956 } 957 } 958 } 959 if (x) { 960 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 961 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 962 } 963 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 964 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 965 ierr = PetscFree(lrows);CHKERRQ(ierr); 966 967 /* only change matrix nonzero state if pattern was allowed to be changed */ 968 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 969 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 970 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 971 } 972 PetscFunctionReturn(0); 973 } 974 975 #undef __FUNCT__ 976 #define __FUNCT__ "MatMult_MPIAIJ" 977 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 978 { 979 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 980 PetscErrorCode ierr; 981 PetscInt nt; 982 983 PetscFunctionBegin; 984 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 985 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 986 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 987 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 988 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 989 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 990 PetscFunctionReturn(0); 991 } 992 993 #undef __FUNCT__ 994 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 995 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 996 { 997 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 998 PetscErrorCode ierr; 999 1000 PetscFunctionBegin; 1001 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1002 PetscFunctionReturn(0); 1003 } 1004 1005 #undef __FUNCT__ 1006 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1007 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1008 { 1009 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1010 PetscErrorCode ierr; 1011 1012 PetscFunctionBegin; 1013 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1014 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1015 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1016 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1017 PetscFunctionReturn(0); 1018 } 1019 1020 #undef __FUNCT__ 1021 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1022 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1023 { 1024 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1025 PetscErrorCode ierr; 1026 PetscBool merged; 1027 1028 PetscFunctionBegin; 1029 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1030 /* do nondiagonal part */ 1031 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1032 if (!merged) { 1033 /* send it on its way */ 1034 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1035 /* do local part */ 1036 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1037 /* receive remote parts: note this assumes the values are not actually */ 1038 /* added in yy until the next line, */ 1039 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1040 } else { 1041 /* do local part */ 1042 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1043 /* send it on its way */ 1044 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1045 /* values actually were received in the Begin() but we need to call this nop */ 1046 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1047 } 1048 PetscFunctionReturn(0); 1049 } 1050 1051 #undef __FUNCT__ 1052 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1053 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1054 { 1055 MPI_Comm comm; 1056 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1057 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1058 IS Me,Notme; 1059 PetscErrorCode ierr; 1060 PetscInt M,N,first,last,*notme,i; 1061 PetscMPIInt size; 1062 1063 PetscFunctionBegin; 1064 /* Easy test: symmetric diagonal block */ 1065 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1066 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1067 if (!*f) PetscFunctionReturn(0); 1068 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1069 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1070 if (size == 1) PetscFunctionReturn(0); 1071 1072 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1073 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1074 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1075 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1076 for (i=0; i<first; i++) notme[i] = i; 1077 for (i=last; i<M; i++) notme[i-last+first] = i; 1078 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1079 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1080 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1081 Aoff = Aoffs[0]; 1082 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1083 Boff = Boffs[0]; 1084 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1085 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1086 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1087 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1088 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1089 ierr = PetscFree(notme);CHKERRQ(ierr); 1090 PetscFunctionReturn(0); 1091 } 1092 1093 #undef __FUNCT__ 1094 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1095 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1096 { 1097 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1098 PetscErrorCode ierr; 1099 1100 PetscFunctionBegin; 1101 /* do nondiagonal part */ 1102 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1103 /* send it on its way */ 1104 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1105 /* do local part */ 1106 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1107 /* receive remote parts */ 1108 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1109 PetscFunctionReturn(0); 1110 } 1111 1112 /* 1113 This only works correctly for square matrices where the subblock A->A is the 1114 diagonal block 1115 */ 1116 #undef __FUNCT__ 1117 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1118 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1119 { 1120 PetscErrorCode ierr; 1121 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1122 1123 PetscFunctionBegin; 1124 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1125 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1126 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatScale_MPIAIJ" 1132 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1139 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatDestroy_MPIAIJ" 1145 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1146 { 1147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1148 PetscErrorCode ierr; 1149 1150 PetscFunctionBegin; 1151 #if defined(PETSC_USE_LOG) 1152 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1153 #endif 1154 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1155 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1156 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1157 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1158 #if defined(PETSC_USE_CTABLE) 1159 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1160 #else 1161 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1162 #endif 1163 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1164 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1165 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1166 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1167 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1168 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1169 1170 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1171 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1172 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1173 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1174 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1175 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1176 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1177 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1178 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1179 #if defined(PETSC_HAVE_ELEMENTAL) 1180 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1181 #endif 1182 PetscFunctionReturn(0); 1183 } 1184 1185 #undef __FUNCT__ 1186 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1187 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1188 { 1189 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1190 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1191 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1192 PetscErrorCode ierr; 1193 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1194 int fd; 1195 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1196 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1197 PetscScalar *column_values; 1198 PetscInt message_count,flowcontrolcount; 1199 FILE *file; 1200 1201 PetscFunctionBegin; 1202 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1203 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1204 nz = A->nz + B->nz; 1205 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1206 if (!rank) { 1207 header[0] = MAT_FILE_CLASSID; 1208 header[1] = mat->rmap->N; 1209 header[2] = mat->cmap->N; 1210 1211 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1212 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1213 /* get largest number of rows any processor has */ 1214 rlen = mat->rmap->n; 1215 range = mat->rmap->range; 1216 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1217 } else { 1218 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 rlen = mat->rmap->n; 1220 } 1221 1222 /* load up the local row counts */ 1223 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1224 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1225 1226 /* store the row lengths to the file */ 1227 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1228 if (!rank) { 1229 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1230 for (i=1; i<size; i++) { 1231 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1232 rlen = range[i+1] - range[i]; 1233 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1234 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1235 } 1236 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1237 } else { 1238 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1239 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1240 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1241 } 1242 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1243 1244 /* load up the local column indices */ 1245 nzmax = nz; /* th processor needs space a largest processor needs */ 1246 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1247 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1248 cnt = 0; 1249 for (i=0; i<mat->rmap->n; i++) { 1250 for (j=B->i[i]; j<B->i[i+1]; j++) { 1251 if ((col = garray[B->j[j]]) > cstart) break; 1252 column_indices[cnt++] = col; 1253 } 1254 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1255 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1256 } 1257 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1258 1259 /* store the column indices to the file */ 1260 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1261 if (!rank) { 1262 MPI_Status status; 1263 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1264 for (i=1; i<size; i++) { 1265 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1266 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1267 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1268 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1269 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1270 } 1271 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1272 } else { 1273 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1274 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1275 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1276 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1277 } 1278 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1279 1280 /* load up the local column values */ 1281 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1282 cnt = 0; 1283 for (i=0; i<mat->rmap->n; i++) { 1284 for (j=B->i[i]; j<B->i[i+1]; j++) { 1285 if (garray[B->j[j]] > cstart) break; 1286 column_values[cnt++] = B->a[j]; 1287 } 1288 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1289 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1290 } 1291 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1292 1293 /* store the column values to the file */ 1294 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1295 if (!rank) { 1296 MPI_Status status; 1297 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1298 for (i=1; i<size; i++) { 1299 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1300 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1301 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1302 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1303 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1304 } 1305 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1306 } else { 1307 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1308 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1309 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1310 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1311 } 1312 ierr = PetscFree(column_values);CHKERRQ(ierr); 1313 1314 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1315 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1316 PetscFunctionReturn(0); 1317 } 1318 1319 #include <petscdraw.h> 1320 #undef __FUNCT__ 1321 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1322 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1323 { 1324 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1325 PetscErrorCode ierr; 1326 PetscMPIInt rank = aij->rank,size = aij->size; 1327 PetscBool isdraw,iascii,isbinary; 1328 PetscViewer sviewer; 1329 PetscViewerFormat format; 1330 1331 PetscFunctionBegin; 1332 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1333 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1334 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1335 if (iascii) { 1336 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1337 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1338 MatInfo info; 1339 PetscBool inodes; 1340 1341 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1342 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1343 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1344 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1345 if (!inodes) { 1346 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1347 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1348 } else { 1349 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1350 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1351 } 1352 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1353 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1354 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1355 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1356 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1357 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1358 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1359 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1360 PetscFunctionReturn(0); 1361 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1362 PetscInt inodecount,inodelimit,*inodes; 1363 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1364 if (inodes) { 1365 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1366 } else { 1367 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1368 } 1369 PetscFunctionReturn(0); 1370 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1371 PetscFunctionReturn(0); 1372 } 1373 } else if (isbinary) { 1374 if (size == 1) { 1375 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1376 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1377 } else { 1378 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1379 } 1380 PetscFunctionReturn(0); 1381 } else if (isdraw) { 1382 PetscDraw draw; 1383 PetscBool isnull; 1384 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1385 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1386 } 1387 1388 { 1389 /* assemble the entire matrix onto first processor. */ 1390 Mat A; 1391 Mat_SeqAIJ *Aloc; 1392 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1393 MatScalar *a; 1394 1395 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1396 if (!rank) { 1397 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1398 } else { 1399 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1400 } 1401 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1402 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1403 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1404 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1405 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1406 1407 /* copy over the A part */ 1408 Aloc = (Mat_SeqAIJ*)aij->A->data; 1409 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1410 row = mat->rmap->rstart; 1411 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1412 for (i=0; i<m; i++) { 1413 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1414 row++; 1415 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1416 } 1417 aj = Aloc->j; 1418 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1419 1420 /* copy over the B part */ 1421 Aloc = (Mat_SeqAIJ*)aij->B->data; 1422 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1423 row = mat->rmap->rstart; 1424 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1425 ct = cols; 1426 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1427 for (i=0; i<m; i++) { 1428 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1429 row++; 1430 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1431 } 1432 ierr = PetscFree(ct);CHKERRQ(ierr); 1433 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1434 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1435 /* 1436 Everyone has to call to draw the matrix since the graphics waits are 1437 synchronized across all processors that share the PetscDraw object 1438 */ 1439 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1440 if (!rank) { 1441 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1442 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1443 } 1444 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1445 ierr = MatDestroy(&A);CHKERRQ(ierr); 1446 } 1447 PetscFunctionReturn(0); 1448 } 1449 1450 #undef __FUNCT__ 1451 #define __FUNCT__ "MatView_MPIAIJ" 1452 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1453 { 1454 PetscErrorCode ierr; 1455 PetscBool iascii,isdraw,issocket,isbinary; 1456 1457 PetscFunctionBegin; 1458 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1459 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1460 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1461 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1462 if (iascii || isdraw || isbinary || issocket) { 1463 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1464 } 1465 PetscFunctionReturn(0); 1466 } 1467 1468 #undef __FUNCT__ 1469 #define __FUNCT__ "MatSOR_MPIAIJ" 1470 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1471 { 1472 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1473 PetscErrorCode ierr; 1474 Vec bb1 = 0; 1475 PetscBool hasop; 1476 1477 PetscFunctionBegin; 1478 if (flag == SOR_APPLY_UPPER) { 1479 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1480 PetscFunctionReturn(0); 1481 } 1482 1483 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1484 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1485 } 1486 1487 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1488 if (flag & SOR_ZERO_INITIAL_GUESS) { 1489 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1490 its--; 1491 } 1492 1493 while (its--) { 1494 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1495 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1496 1497 /* update rhs: bb1 = bb - B*x */ 1498 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1499 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1500 1501 /* local sweep */ 1502 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1503 } 1504 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1505 if (flag & SOR_ZERO_INITIAL_GUESS) { 1506 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1507 its--; 1508 } 1509 while (its--) { 1510 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1511 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1512 1513 /* update rhs: bb1 = bb - B*x */ 1514 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1515 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1516 1517 /* local sweep */ 1518 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1519 } 1520 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1521 if (flag & SOR_ZERO_INITIAL_GUESS) { 1522 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1523 its--; 1524 } 1525 while (its--) { 1526 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1527 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1528 1529 /* update rhs: bb1 = bb - B*x */ 1530 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1531 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1532 1533 /* local sweep */ 1534 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1535 } 1536 } else if (flag & SOR_EISENSTAT) { 1537 Vec xx1; 1538 1539 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1540 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1541 1542 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1543 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1544 if (!mat->diag) { 1545 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1546 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1547 } 1548 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1549 if (hasop) { 1550 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1551 } else { 1552 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1553 } 1554 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1555 1556 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1557 1558 /* local sweep */ 1559 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1560 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1561 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1562 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1563 1564 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1565 PetscFunctionReturn(0); 1566 } 1567 1568 #undef __FUNCT__ 1569 #define __FUNCT__ "MatPermute_MPIAIJ" 1570 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1571 { 1572 Mat aA,aB,Aperm; 1573 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1574 PetscScalar *aa,*ba; 1575 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1576 PetscSF rowsf,sf; 1577 IS parcolp = NULL; 1578 PetscBool done; 1579 PetscErrorCode ierr; 1580 1581 PetscFunctionBegin; 1582 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1583 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1584 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1585 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1586 1587 /* Invert row permutation to find out where my rows should go */ 1588 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1589 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1590 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1591 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1592 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1593 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1594 1595 /* Invert column permutation to find out where my columns should go */ 1596 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1597 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1598 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1599 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1600 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1601 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1602 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1603 1604 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1605 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1606 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1607 1608 /* Find out where my gcols should go */ 1609 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1610 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1611 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1612 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1613 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1614 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1615 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1616 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1617 1618 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1619 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1620 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1621 for (i=0; i<m; i++) { 1622 PetscInt row = rdest[i],rowner; 1623 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1624 for (j=ai[i]; j<ai[i+1]; j++) { 1625 PetscInt cowner,col = cdest[aj[j]]; 1626 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1627 if (rowner == cowner) dnnz[i]++; 1628 else onnz[i]++; 1629 } 1630 for (j=bi[i]; j<bi[i+1]; j++) { 1631 PetscInt cowner,col = gcdest[bj[j]]; 1632 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1633 if (rowner == cowner) dnnz[i]++; 1634 else onnz[i]++; 1635 } 1636 } 1637 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1638 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1639 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1640 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1641 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1642 1643 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1644 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1645 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1646 for (i=0; i<m; i++) { 1647 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1648 PetscInt j0,rowlen; 1649 rowlen = ai[i+1] - ai[i]; 1650 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1651 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1652 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1653 } 1654 rowlen = bi[i+1] - bi[i]; 1655 for (j0=j=0; j<rowlen; j0=j) { 1656 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1657 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1658 } 1659 } 1660 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1661 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1662 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1663 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1664 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1665 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1666 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1667 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1668 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1669 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1670 *B = Aperm; 1671 PetscFunctionReturn(0); 1672 } 1673 1674 #undef __FUNCT__ 1675 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1676 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1677 { 1678 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1679 Mat A = mat->A,B = mat->B; 1680 PetscErrorCode ierr; 1681 PetscReal isend[5],irecv[5]; 1682 1683 PetscFunctionBegin; 1684 info->block_size = 1.0; 1685 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1686 1687 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1688 isend[3] = info->memory; isend[4] = info->mallocs; 1689 1690 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1691 1692 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1693 isend[3] += info->memory; isend[4] += info->mallocs; 1694 if (flag == MAT_LOCAL) { 1695 info->nz_used = isend[0]; 1696 info->nz_allocated = isend[1]; 1697 info->nz_unneeded = isend[2]; 1698 info->memory = isend[3]; 1699 info->mallocs = isend[4]; 1700 } else if (flag == MAT_GLOBAL_MAX) { 1701 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1702 1703 info->nz_used = irecv[0]; 1704 info->nz_allocated = irecv[1]; 1705 info->nz_unneeded = irecv[2]; 1706 info->memory = irecv[3]; 1707 info->mallocs = irecv[4]; 1708 } else if (flag == MAT_GLOBAL_SUM) { 1709 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1710 1711 info->nz_used = irecv[0]; 1712 info->nz_allocated = irecv[1]; 1713 info->nz_unneeded = irecv[2]; 1714 info->memory = irecv[3]; 1715 info->mallocs = irecv[4]; 1716 } 1717 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1718 info->fill_ratio_needed = 0; 1719 info->factor_mallocs = 0; 1720 PetscFunctionReturn(0); 1721 } 1722 1723 #undef __FUNCT__ 1724 #define __FUNCT__ "MatSetOption_MPIAIJ" 1725 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1726 { 1727 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1728 PetscErrorCode ierr; 1729 1730 PetscFunctionBegin; 1731 switch (op) { 1732 case MAT_NEW_NONZERO_LOCATIONS: 1733 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1734 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1735 case MAT_KEEP_NONZERO_PATTERN: 1736 case MAT_NEW_NONZERO_LOCATION_ERR: 1737 case MAT_USE_INODES: 1738 case MAT_IGNORE_ZERO_ENTRIES: 1739 MatCheckPreallocated(A,1); 1740 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1741 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1742 break; 1743 case MAT_ROW_ORIENTED: 1744 a->roworiented = flg; 1745 1746 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1747 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1748 break; 1749 case MAT_NEW_DIAGONALS: 1750 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1751 break; 1752 case MAT_IGNORE_OFF_PROC_ENTRIES: 1753 a->donotstash = flg; 1754 break; 1755 case MAT_SPD: 1756 A->spd_set = PETSC_TRUE; 1757 A->spd = flg; 1758 if (flg) { 1759 A->symmetric = PETSC_TRUE; 1760 A->structurally_symmetric = PETSC_TRUE; 1761 A->symmetric_set = PETSC_TRUE; 1762 A->structurally_symmetric_set = PETSC_TRUE; 1763 } 1764 break; 1765 case MAT_SYMMETRIC: 1766 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1767 break; 1768 case MAT_STRUCTURALLY_SYMMETRIC: 1769 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1770 break; 1771 case MAT_HERMITIAN: 1772 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1773 break; 1774 case MAT_SYMMETRY_ETERNAL: 1775 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1776 break; 1777 default: 1778 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1779 } 1780 PetscFunctionReturn(0); 1781 } 1782 1783 #undef __FUNCT__ 1784 #define __FUNCT__ "MatGetRow_MPIAIJ" 1785 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1786 { 1787 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1788 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1789 PetscErrorCode ierr; 1790 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1791 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1792 PetscInt *cmap,*idx_p; 1793 1794 PetscFunctionBegin; 1795 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1796 mat->getrowactive = PETSC_TRUE; 1797 1798 if (!mat->rowvalues && (idx || v)) { 1799 /* 1800 allocate enough space to hold information from the longest row. 1801 */ 1802 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1803 PetscInt max = 1,tmp; 1804 for (i=0; i<matin->rmap->n; i++) { 1805 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1806 if (max < tmp) max = tmp; 1807 } 1808 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1809 } 1810 1811 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1812 lrow = row - rstart; 1813 1814 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1815 if (!v) {pvA = 0; pvB = 0;} 1816 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1817 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1818 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1819 nztot = nzA + nzB; 1820 1821 cmap = mat->garray; 1822 if (v || idx) { 1823 if (nztot) { 1824 /* Sort by increasing column numbers, assuming A and B already sorted */ 1825 PetscInt imark = -1; 1826 if (v) { 1827 *v = v_p = mat->rowvalues; 1828 for (i=0; i<nzB; i++) { 1829 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1830 else break; 1831 } 1832 imark = i; 1833 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1834 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1835 } 1836 if (idx) { 1837 *idx = idx_p = mat->rowindices; 1838 if (imark > -1) { 1839 for (i=0; i<imark; i++) { 1840 idx_p[i] = cmap[cworkB[i]]; 1841 } 1842 } else { 1843 for (i=0; i<nzB; i++) { 1844 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1845 else break; 1846 } 1847 imark = i; 1848 } 1849 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1850 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1851 } 1852 } else { 1853 if (idx) *idx = 0; 1854 if (v) *v = 0; 1855 } 1856 } 1857 *nz = nztot; 1858 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1859 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1860 PetscFunctionReturn(0); 1861 } 1862 1863 #undef __FUNCT__ 1864 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1865 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1866 { 1867 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1868 1869 PetscFunctionBegin; 1870 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1871 aij->getrowactive = PETSC_FALSE; 1872 PetscFunctionReturn(0); 1873 } 1874 1875 #undef __FUNCT__ 1876 #define __FUNCT__ "MatNorm_MPIAIJ" 1877 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1878 { 1879 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1880 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1881 PetscErrorCode ierr; 1882 PetscInt i,j,cstart = mat->cmap->rstart; 1883 PetscReal sum = 0.0; 1884 MatScalar *v; 1885 1886 PetscFunctionBegin; 1887 if (aij->size == 1) { 1888 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1889 } else { 1890 if (type == NORM_FROBENIUS) { 1891 v = amat->a; 1892 for (i=0; i<amat->nz; i++) { 1893 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1894 } 1895 v = bmat->a; 1896 for (i=0; i<bmat->nz; i++) { 1897 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1898 } 1899 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1900 *norm = PetscSqrtReal(*norm); 1901 } else if (type == NORM_1) { /* max column norm */ 1902 PetscReal *tmp,*tmp2; 1903 PetscInt *jj,*garray = aij->garray; 1904 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1905 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1906 *norm = 0.0; 1907 v = amat->a; jj = amat->j; 1908 for (j=0; j<amat->nz; j++) { 1909 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1910 } 1911 v = bmat->a; jj = bmat->j; 1912 for (j=0; j<bmat->nz; j++) { 1913 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1914 } 1915 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1916 for (j=0; j<mat->cmap->N; j++) { 1917 if (tmp2[j] > *norm) *norm = tmp2[j]; 1918 } 1919 ierr = PetscFree(tmp);CHKERRQ(ierr); 1920 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1921 } else if (type == NORM_INFINITY) { /* max row norm */ 1922 PetscReal ntemp = 0.0; 1923 for (j=0; j<aij->A->rmap->n; j++) { 1924 v = amat->a + amat->i[j]; 1925 sum = 0.0; 1926 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1927 sum += PetscAbsScalar(*v); v++; 1928 } 1929 v = bmat->a + bmat->i[j]; 1930 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1931 sum += PetscAbsScalar(*v); v++; 1932 } 1933 if (sum > ntemp) ntemp = sum; 1934 } 1935 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1936 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1937 } 1938 PetscFunctionReturn(0); 1939 } 1940 1941 #undef __FUNCT__ 1942 #define __FUNCT__ "MatTranspose_MPIAIJ" 1943 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1944 { 1945 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1946 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1947 PetscErrorCode ierr; 1948 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1949 PetscInt cstart = A->cmap->rstart,ncol; 1950 Mat B; 1951 MatScalar *array; 1952 1953 PetscFunctionBegin; 1954 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1955 1956 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1957 ai = Aloc->i; aj = Aloc->j; 1958 bi = Bloc->i; bj = Bloc->j; 1959 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1960 PetscInt *d_nnz,*g_nnz,*o_nnz; 1961 PetscSFNode *oloc; 1962 PETSC_UNUSED PetscSF sf; 1963 1964 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1965 /* compute d_nnz for preallocation */ 1966 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1967 for (i=0; i<ai[ma]; i++) { 1968 d_nnz[aj[i]]++; 1969 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1970 } 1971 /* compute local off-diagonal contributions */ 1972 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1973 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1974 /* map those to global */ 1975 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1976 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1977 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1978 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1979 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1980 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1981 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1982 1983 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1984 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1985 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1986 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1987 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1988 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1989 } else { 1990 B = *matout; 1991 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1992 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1993 } 1994 1995 /* copy over the A part */ 1996 array = Aloc->a; 1997 row = A->rmap->rstart; 1998 for (i=0; i<ma; i++) { 1999 ncol = ai[i+1]-ai[i]; 2000 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2001 row++; 2002 array += ncol; aj += ncol; 2003 } 2004 aj = Aloc->j; 2005 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2006 2007 /* copy over the B part */ 2008 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2009 array = Bloc->a; 2010 row = A->rmap->rstart; 2011 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2012 cols_tmp = cols; 2013 for (i=0; i<mb; i++) { 2014 ncol = bi[i+1]-bi[i]; 2015 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2016 row++; 2017 array += ncol; cols_tmp += ncol; 2018 } 2019 ierr = PetscFree(cols);CHKERRQ(ierr); 2020 2021 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2022 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2023 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2024 *matout = B; 2025 } else { 2026 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2027 } 2028 PetscFunctionReturn(0); 2029 } 2030 2031 #undef __FUNCT__ 2032 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2033 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2034 { 2035 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2036 Mat a = aij->A,b = aij->B; 2037 PetscErrorCode ierr; 2038 PetscInt s1,s2,s3; 2039 2040 PetscFunctionBegin; 2041 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2042 if (rr) { 2043 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2044 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2045 /* Overlap communication with computation. */ 2046 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2047 } 2048 if (ll) { 2049 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2050 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2051 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2052 } 2053 /* scale the diagonal block */ 2054 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2055 2056 if (rr) { 2057 /* Do a scatter end and then right scale the off-diagonal block */ 2058 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2059 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2060 } 2061 PetscFunctionReturn(0); 2062 } 2063 2064 #undef __FUNCT__ 2065 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2066 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2067 { 2068 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2069 PetscErrorCode ierr; 2070 2071 PetscFunctionBegin; 2072 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatEqual_MPIAIJ" 2078 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2079 { 2080 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2081 Mat a,b,c,d; 2082 PetscBool flg; 2083 PetscErrorCode ierr; 2084 2085 PetscFunctionBegin; 2086 a = matA->A; b = matA->B; 2087 c = matB->A; d = matB->B; 2088 2089 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2090 if (flg) { 2091 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2092 } 2093 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2094 PetscFunctionReturn(0); 2095 } 2096 2097 #undef __FUNCT__ 2098 #define __FUNCT__ "MatCopy_MPIAIJ" 2099 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2100 { 2101 PetscErrorCode ierr; 2102 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2103 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2104 2105 PetscFunctionBegin; 2106 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2107 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2108 /* because of the column compression in the off-processor part of the matrix a->B, 2109 the number of columns in a->B and b->B may be different, hence we cannot call 2110 the MatCopy() directly on the two parts. If need be, we can provide a more 2111 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2112 then copying the submatrices */ 2113 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2114 } else { 2115 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2116 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2117 } 2118 PetscFunctionReturn(0); 2119 } 2120 2121 #undef __FUNCT__ 2122 #define __FUNCT__ "MatSetUp_MPIAIJ" 2123 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2124 { 2125 PetscErrorCode ierr; 2126 2127 PetscFunctionBegin; 2128 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2129 PetscFunctionReturn(0); 2130 } 2131 2132 /* 2133 Computes the number of nonzeros per row needed for preallocation when X and Y 2134 have different nonzero structure. 2135 */ 2136 #undef __FUNCT__ 2137 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2138 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2139 { 2140 PetscInt i,j,k,nzx,nzy; 2141 2142 PetscFunctionBegin; 2143 /* Set the number of nonzeros in the new matrix */ 2144 for (i=0; i<m; i++) { 2145 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2146 nzx = xi[i+1] - xi[i]; 2147 nzy = yi[i+1] - yi[i]; 2148 nnz[i] = 0; 2149 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2150 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2151 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2152 nnz[i]++; 2153 } 2154 for (; k<nzy; k++) nnz[i]++; 2155 } 2156 PetscFunctionReturn(0); 2157 } 2158 2159 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2160 #undef __FUNCT__ 2161 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2162 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2163 { 2164 PetscErrorCode ierr; 2165 PetscInt m = Y->rmap->N; 2166 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2167 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2168 2169 PetscFunctionBegin; 2170 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2171 PetscFunctionReturn(0); 2172 } 2173 2174 #undef __FUNCT__ 2175 #define __FUNCT__ "MatAXPY_MPIAIJ" 2176 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2177 { 2178 PetscErrorCode ierr; 2179 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2180 PetscBLASInt bnz,one=1; 2181 Mat_SeqAIJ *x,*y; 2182 2183 PetscFunctionBegin; 2184 if (str == SAME_NONZERO_PATTERN) { 2185 PetscScalar alpha = a; 2186 x = (Mat_SeqAIJ*)xx->A->data; 2187 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2188 y = (Mat_SeqAIJ*)yy->A->data; 2189 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2190 x = (Mat_SeqAIJ*)xx->B->data; 2191 y = (Mat_SeqAIJ*)yy->B->data; 2192 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2193 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2194 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2195 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2196 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2197 } else { 2198 Mat B; 2199 PetscInt *nnz_d,*nnz_o; 2200 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2201 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2202 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2203 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2204 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2205 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2206 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2207 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2208 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2209 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2210 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2211 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2212 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2213 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2214 } 2215 PetscFunctionReturn(0); 2216 } 2217 2218 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2219 2220 #undef __FUNCT__ 2221 #define __FUNCT__ "MatConjugate_MPIAIJ" 2222 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2223 { 2224 #if defined(PETSC_USE_COMPLEX) 2225 PetscErrorCode ierr; 2226 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2227 2228 PetscFunctionBegin; 2229 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2230 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2231 #else 2232 PetscFunctionBegin; 2233 #endif 2234 PetscFunctionReturn(0); 2235 } 2236 2237 #undef __FUNCT__ 2238 #define __FUNCT__ "MatRealPart_MPIAIJ" 2239 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2240 { 2241 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2242 PetscErrorCode ierr; 2243 2244 PetscFunctionBegin; 2245 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2246 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2247 PetscFunctionReturn(0); 2248 } 2249 2250 #undef __FUNCT__ 2251 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2252 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2253 { 2254 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2255 PetscErrorCode ierr; 2256 2257 PetscFunctionBegin; 2258 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2259 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2260 PetscFunctionReturn(0); 2261 } 2262 2263 #if defined(PETSC_HAVE_PBGL) 2264 2265 #include <boost/parallel/mpi/bsp_process_group.hpp> 2266 #include <boost/graph/distributed/ilu_default_graph.hpp> 2267 #include <boost/graph/distributed/ilu_0_block.hpp> 2268 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2269 #include <boost/graph/distributed/petsc/interface.hpp> 2270 #include <boost/multi_array.hpp> 2271 #include <boost/parallel/distributed_property_map->hpp> 2272 2273 #undef __FUNCT__ 2274 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2275 /* 2276 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2277 */ 2278 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2279 { 2280 namespace petsc = boost::distributed::petsc; 2281 2282 namespace graph_dist = boost::graph::distributed; 2283 using boost::graph::distributed::ilu_default::process_group_type; 2284 using boost::graph::ilu_permuted; 2285 2286 PetscBool row_identity, col_identity; 2287 PetscContainer c; 2288 PetscInt m, n, M, N; 2289 PetscErrorCode ierr; 2290 2291 PetscFunctionBegin; 2292 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2293 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2294 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2295 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2296 2297 process_group_type pg; 2298 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2299 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2300 lgraph_type& level_graph = *lgraph_p; 2301 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2302 2303 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2304 ilu_permuted(level_graph); 2305 2306 /* put together the new matrix */ 2307 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2308 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2309 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2310 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2311 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2312 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2313 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2314 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2315 2316 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2317 ierr = PetscContainerSetPointer(c, lgraph_p); 2318 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2319 ierr = PetscContainerDestroy(&c); 2320 PetscFunctionReturn(0); 2321 } 2322 2323 #undef __FUNCT__ 2324 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2325 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2326 { 2327 PetscFunctionBegin; 2328 PetscFunctionReturn(0); 2329 } 2330 2331 #undef __FUNCT__ 2332 #define __FUNCT__ "MatSolve_MPIAIJ" 2333 /* 2334 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2335 */ 2336 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2337 { 2338 namespace graph_dist = boost::graph::distributed; 2339 2340 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2341 lgraph_type *lgraph_p; 2342 PetscContainer c; 2343 PetscErrorCode ierr; 2344 2345 PetscFunctionBegin; 2346 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2347 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2348 ierr = VecCopy(b, x);CHKERRQ(ierr); 2349 2350 PetscScalar *array_x; 2351 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2352 PetscInt sx; 2353 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2354 2355 PetscScalar *array_b; 2356 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2357 PetscInt sb; 2358 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2359 2360 lgraph_type& level_graph = *lgraph_p; 2361 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2362 2363 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2364 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2365 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2366 2367 typedef boost::iterator_property_map<array_ref_type::iterator, 2368 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2369 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2370 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2371 2372 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2373 PetscFunctionReturn(0); 2374 } 2375 #endif 2376 2377 #undef __FUNCT__ 2378 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2379 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2380 { 2381 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2382 PetscErrorCode ierr; 2383 PetscInt i,*idxb = 0; 2384 PetscScalar *va,*vb; 2385 Vec vtmp; 2386 2387 PetscFunctionBegin; 2388 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2389 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2390 if (idx) { 2391 for (i=0; i<A->rmap->n; i++) { 2392 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2393 } 2394 } 2395 2396 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2397 if (idx) { 2398 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2399 } 2400 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2401 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2402 2403 for (i=0; i<A->rmap->n; i++) { 2404 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2405 va[i] = vb[i]; 2406 if (idx) idx[i] = a->garray[idxb[i]]; 2407 } 2408 } 2409 2410 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2411 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2412 ierr = PetscFree(idxb);CHKERRQ(ierr); 2413 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2414 PetscFunctionReturn(0); 2415 } 2416 2417 #undef __FUNCT__ 2418 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2419 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2420 { 2421 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2422 PetscErrorCode ierr; 2423 PetscInt i,*idxb = 0; 2424 PetscScalar *va,*vb; 2425 Vec vtmp; 2426 2427 PetscFunctionBegin; 2428 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2429 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2430 if (idx) { 2431 for (i=0; i<A->cmap->n; i++) { 2432 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2433 } 2434 } 2435 2436 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2437 if (idx) { 2438 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2439 } 2440 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2441 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2442 2443 for (i=0; i<A->rmap->n; i++) { 2444 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2445 va[i] = vb[i]; 2446 if (idx) idx[i] = a->garray[idxb[i]]; 2447 } 2448 } 2449 2450 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2451 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2452 ierr = PetscFree(idxb);CHKERRQ(ierr); 2453 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2454 PetscFunctionReturn(0); 2455 } 2456 2457 #undef __FUNCT__ 2458 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2459 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2460 { 2461 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2462 PetscInt n = A->rmap->n; 2463 PetscInt cstart = A->cmap->rstart; 2464 PetscInt *cmap = mat->garray; 2465 PetscInt *diagIdx, *offdiagIdx; 2466 Vec diagV, offdiagV; 2467 PetscScalar *a, *diagA, *offdiagA; 2468 PetscInt r; 2469 PetscErrorCode ierr; 2470 2471 PetscFunctionBegin; 2472 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2473 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2474 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2475 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2476 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2477 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2478 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2479 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2480 for (r = 0; r < n; ++r) { 2481 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2482 a[r] = diagA[r]; 2483 idx[r] = cstart + diagIdx[r]; 2484 } else { 2485 a[r] = offdiagA[r]; 2486 idx[r] = cmap[offdiagIdx[r]]; 2487 } 2488 } 2489 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2490 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2491 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2492 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2493 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2494 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2495 PetscFunctionReturn(0); 2496 } 2497 2498 #undef __FUNCT__ 2499 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2500 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2501 { 2502 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2503 PetscInt n = A->rmap->n; 2504 PetscInt cstart = A->cmap->rstart; 2505 PetscInt *cmap = mat->garray; 2506 PetscInt *diagIdx, *offdiagIdx; 2507 Vec diagV, offdiagV; 2508 PetscScalar *a, *diagA, *offdiagA; 2509 PetscInt r; 2510 PetscErrorCode ierr; 2511 2512 PetscFunctionBegin; 2513 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2514 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2515 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2516 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2517 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2518 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2519 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2520 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2521 for (r = 0; r < n; ++r) { 2522 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2523 a[r] = diagA[r]; 2524 idx[r] = cstart + diagIdx[r]; 2525 } else { 2526 a[r] = offdiagA[r]; 2527 idx[r] = cmap[offdiagIdx[r]]; 2528 } 2529 } 2530 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2531 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2532 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2533 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2534 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2535 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2536 PetscFunctionReturn(0); 2537 } 2538 2539 #undef __FUNCT__ 2540 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2541 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2542 { 2543 PetscErrorCode ierr; 2544 Mat *dummy; 2545 2546 PetscFunctionBegin; 2547 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2548 *newmat = *dummy; 2549 ierr = PetscFree(dummy);CHKERRQ(ierr); 2550 PetscFunctionReturn(0); 2551 } 2552 2553 #undef __FUNCT__ 2554 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2555 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2556 { 2557 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2558 PetscErrorCode ierr; 2559 2560 PetscFunctionBegin; 2561 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2562 PetscFunctionReturn(0); 2563 } 2564 2565 #undef __FUNCT__ 2566 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2567 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2568 { 2569 PetscErrorCode ierr; 2570 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2571 2572 PetscFunctionBegin; 2573 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2574 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2575 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2576 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2577 PetscFunctionReturn(0); 2578 } 2579 2580 #undef __FUNCT__ 2581 #define __FUNCT__ "MatShift_MPIAIJ" 2582 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2583 { 2584 PetscErrorCode ierr; 2585 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2586 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data,*bij = (Mat_SeqAIJ*)maij->B->data; 2587 2588 PetscFunctionBegin; 2589 if (!aij->nz && !bij->nz) { 2590 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2591 } 2592 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2593 PetscFunctionReturn(0); 2594 } 2595 2596 /* -------------------------------------------------------------------*/ 2597 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2598 MatGetRow_MPIAIJ, 2599 MatRestoreRow_MPIAIJ, 2600 MatMult_MPIAIJ, 2601 /* 4*/ MatMultAdd_MPIAIJ, 2602 MatMultTranspose_MPIAIJ, 2603 MatMultTransposeAdd_MPIAIJ, 2604 #if defined(PETSC_HAVE_PBGL) 2605 MatSolve_MPIAIJ, 2606 #else 2607 0, 2608 #endif 2609 0, 2610 0, 2611 /*10*/ 0, 2612 0, 2613 0, 2614 MatSOR_MPIAIJ, 2615 MatTranspose_MPIAIJ, 2616 /*15*/ MatGetInfo_MPIAIJ, 2617 MatEqual_MPIAIJ, 2618 MatGetDiagonal_MPIAIJ, 2619 MatDiagonalScale_MPIAIJ, 2620 MatNorm_MPIAIJ, 2621 /*20*/ MatAssemblyBegin_MPIAIJ, 2622 MatAssemblyEnd_MPIAIJ, 2623 MatSetOption_MPIAIJ, 2624 MatZeroEntries_MPIAIJ, 2625 /*24*/ MatZeroRows_MPIAIJ, 2626 0, 2627 #if defined(PETSC_HAVE_PBGL) 2628 0, 2629 #else 2630 0, 2631 #endif 2632 0, 2633 0, 2634 /*29*/ MatSetUp_MPIAIJ, 2635 #if defined(PETSC_HAVE_PBGL) 2636 0, 2637 #else 2638 0, 2639 #endif 2640 0, 2641 0, 2642 0, 2643 /*34*/ MatDuplicate_MPIAIJ, 2644 0, 2645 0, 2646 0, 2647 0, 2648 /*39*/ MatAXPY_MPIAIJ, 2649 MatGetSubMatrices_MPIAIJ, 2650 MatIncreaseOverlap_MPIAIJ, 2651 MatGetValues_MPIAIJ, 2652 MatCopy_MPIAIJ, 2653 /*44*/ MatGetRowMax_MPIAIJ, 2654 MatScale_MPIAIJ, 2655 MatShift_MPIAIJ, 2656 MatDiagonalSet_MPIAIJ, 2657 MatZeroRowsColumns_MPIAIJ, 2658 /*49*/ MatSetRandom_MPIAIJ, 2659 0, 2660 0, 2661 0, 2662 0, 2663 /*54*/ MatFDColoringCreate_MPIXAIJ, 2664 0, 2665 MatSetUnfactored_MPIAIJ, 2666 MatPermute_MPIAIJ, 2667 0, 2668 /*59*/ MatGetSubMatrix_MPIAIJ, 2669 MatDestroy_MPIAIJ, 2670 MatView_MPIAIJ, 2671 0, 2672 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2673 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2674 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2675 0, 2676 0, 2677 0, 2678 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2679 MatGetRowMinAbs_MPIAIJ, 2680 0, 2681 MatSetColoring_MPIAIJ, 2682 0, 2683 MatSetValuesAdifor_MPIAIJ, 2684 /*75*/ MatFDColoringApply_AIJ, 2685 0, 2686 0, 2687 0, 2688 MatFindZeroDiagonals_MPIAIJ, 2689 /*80*/ 0, 2690 0, 2691 0, 2692 /*83*/ MatLoad_MPIAIJ, 2693 0, 2694 0, 2695 0, 2696 0, 2697 0, 2698 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2699 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2700 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2701 MatPtAP_MPIAIJ_MPIAIJ, 2702 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2703 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2704 0, 2705 0, 2706 0, 2707 0, 2708 /*99*/ 0, 2709 0, 2710 0, 2711 MatConjugate_MPIAIJ, 2712 0, 2713 /*104*/MatSetValuesRow_MPIAIJ, 2714 MatRealPart_MPIAIJ, 2715 MatImaginaryPart_MPIAIJ, 2716 0, 2717 0, 2718 /*109*/0, 2719 0, 2720 MatGetRowMin_MPIAIJ, 2721 0, 2722 0, 2723 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2724 0, 2725 0, 2726 0, 2727 0, 2728 /*119*/0, 2729 0, 2730 0, 2731 0, 2732 MatGetMultiProcBlock_MPIAIJ, 2733 /*124*/MatFindNonzeroRows_MPIAIJ, 2734 MatGetColumnNorms_MPIAIJ, 2735 MatInvertBlockDiagonal_MPIAIJ, 2736 0, 2737 MatGetSubMatricesMPI_MPIAIJ, 2738 /*129*/0, 2739 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2740 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2741 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2742 0, 2743 /*134*/0, 2744 0, 2745 0, 2746 0, 2747 0, 2748 /*139*/0, 2749 0, 2750 0, 2751 MatFDColoringSetUp_MPIXAIJ, 2752 MatFindOffBlockDiagonalEntries_MPIAIJ, 2753 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2754 }; 2755 2756 /* ----------------------------------------------------------------------------------------*/ 2757 2758 #undef __FUNCT__ 2759 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2760 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2761 { 2762 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2763 PetscErrorCode ierr; 2764 2765 PetscFunctionBegin; 2766 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2767 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2768 PetscFunctionReturn(0); 2769 } 2770 2771 #undef __FUNCT__ 2772 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2773 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2774 { 2775 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2776 PetscErrorCode ierr; 2777 2778 PetscFunctionBegin; 2779 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2780 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2781 PetscFunctionReturn(0); 2782 } 2783 2784 #undef __FUNCT__ 2785 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2786 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2787 { 2788 Mat_MPIAIJ *b; 2789 PetscErrorCode ierr; 2790 2791 PetscFunctionBegin; 2792 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2793 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2794 b = (Mat_MPIAIJ*)B->data; 2795 2796 if (!B->preallocated) { 2797 /* Explicitly create 2 MATSEQAIJ matrices. */ 2798 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2799 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2800 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2801 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2802 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2803 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2804 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2805 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2806 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2807 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2808 } 2809 2810 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2811 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2812 B->preallocated = PETSC_TRUE; 2813 PetscFunctionReturn(0); 2814 } 2815 2816 #undef __FUNCT__ 2817 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2818 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2819 { 2820 Mat mat; 2821 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2822 PetscErrorCode ierr; 2823 2824 PetscFunctionBegin; 2825 *newmat = 0; 2826 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2827 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2828 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2829 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2830 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2831 a = (Mat_MPIAIJ*)mat->data; 2832 2833 mat->factortype = matin->factortype; 2834 mat->assembled = PETSC_TRUE; 2835 mat->insertmode = NOT_SET_VALUES; 2836 mat->preallocated = PETSC_TRUE; 2837 2838 a->size = oldmat->size; 2839 a->rank = oldmat->rank; 2840 a->donotstash = oldmat->donotstash; 2841 a->roworiented = oldmat->roworiented; 2842 a->rowindices = 0; 2843 a->rowvalues = 0; 2844 a->getrowactive = PETSC_FALSE; 2845 2846 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2847 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2848 2849 if (oldmat->colmap) { 2850 #if defined(PETSC_USE_CTABLE) 2851 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2852 #else 2853 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2854 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2855 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2856 #endif 2857 } else a->colmap = 0; 2858 if (oldmat->garray) { 2859 PetscInt len; 2860 len = oldmat->B->cmap->n; 2861 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2862 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2863 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2864 } else a->garray = 0; 2865 2866 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2867 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2868 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2869 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2870 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2871 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2872 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2873 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2874 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2875 *newmat = mat; 2876 PetscFunctionReturn(0); 2877 } 2878 2879 2880 2881 #undef __FUNCT__ 2882 #define __FUNCT__ "MatLoad_MPIAIJ" 2883 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2884 { 2885 PetscScalar *vals,*svals; 2886 MPI_Comm comm; 2887 PetscErrorCode ierr; 2888 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2889 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2890 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2891 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2892 PetscInt cend,cstart,n,*rowners; 2893 int fd; 2894 PetscInt bs = newMat->rmap->bs; 2895 2896 PetscFunctionBegin; 2897 /* force binary viewer to load .info file if it has not yet done so */ 2898 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2899 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2900 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2901 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2902 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2903 if (!rank) { 2904 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2905 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2906 } 2907 2908 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2909 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2910 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2911 if (bs < 0) bs = 1; 2912 2913 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2914 M = header[1]; N = header[2]; 2915 2916 /* If global sizes are set, check if they are consistent with that given in the file */ 2917 if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M); 2918 if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N); 2919 2920 /* determine ownership of all (block) rows */ 2921 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2922 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2923 else m = newMat->rmap->n; /* Set by user */ 2924 2925 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2926 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2927 2928 /* First process needs enough room for process with most rows */ 2929 if (!rank) { 2930 mmax = rowners[1]; 2931 for (i=2; i<=size; i++) { 2932 mmax = PetscMax(mmax, rowners[i]); 2933 } 2934 } else mmax = -1; /* unused, but compilers complain */ 2935 2936 rowners[0] = 0; 2937 for (i=2; i<=size; i++) { 2938 rowners[i] += rowners[i-1]; 2939 } 2940 rstart = rowners[rank]; 2941 rend = rowners[rank+1]; 2942 2943 /* distribute row lengths to all processors */ 2944 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2945 if (!rank) { 2946 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2947 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2948 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2949 for (j=0; j<m; j++) { 2950 procsnz[0] += ourlens[j]; 2951 } 2952 for (i=1; i<size; i++) { 2953 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2954 /* calculate the number of nonzeros on each processor */ 2955 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2956 procsnz[i] += rowlengths[j]; 2957 } 2958 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2959 } 2960 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2961 } else { 2962 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2963 } 2964 2965 if (!rank) { 2966 /* determine max buffer needed and allocate it */ 2967 maxnz = 0; 2968 for (i=0; i<size; i++) { 2969 maxnz = PetscMax(maxnz,procsnz[i]); 2970 } 2971 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2972 2973 /* read in my part of the matrix column indices */ 2974 nz = procsnz[0]; 2975 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2976 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2977 2978 /* read in every one elses and ship off */ 2979 for (i=1; i<size; i++) { 2980 nz = procsnz[i]; 2981 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2982 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2983 } 2984 ierr = PetscFree(cols);CHKERRQ(ierr); 2985 } else { 2986 /* determine buffer space needed for message */ 2987 nz = 0; 2988 for (i=0; i<m; i++) { 2989 nz += ourlens[i]; 2990 } 2991 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2992 2993 /* receive message of column indices*/ 2994 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2995 } 2996 2997 /* determine column ownership if matrix is not square */ 2998 if (N != M) { 2999 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3000 else n = newMat->cmap->n; 3001 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3002 cstart = cend - n; 3003 } else { 3004 cstart = rstart; 3005 cend = rend; 3006 n = cend - cstart; 3007 } 3008 3009 /* loop over local rows, determining number of off diagonal entries */ 3010 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3011 jj = 0; 3012 for (i=0; i<m; i++) { 3013 for (j=0; j<ourlens[i]; j++) { 3014 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3015 jj++; 3016 } 3017 } 3018 3019 for (i=0; i<m; i++) { 3020 ourlens[i] -= offlens[i]; 3021 } 3022 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3023 3024 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3025 3026 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3027 3028 for (i=0; i<m; i++) { 3029 ourlens[i] += offlens[i]; 3030 } 3031 3032 if (!rank) { 3033 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3034 3035 /* read in my part of the matrix numerical values */ 3036 nz = procsnz[0]; 3037 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3038 3039 /* insert into matrix */ 3040 jj = rstart; 3041 smycols = mycols; 3042 svals = vals; 3043 for (i=0; i<m; i++) { 3044 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3045 smycols += ourlens[i]; 3046 svals += ourlens[i]; 3047 jj++; 3048 } 3049 3050 /* read in other processors and ship out */ 3051 for (i=1; i<size; i++) { 3052 nz = procsnz[i]; 3053 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3054 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3055 } 3056 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3057 } else { 3058 /* receive numeric values */ 3059 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3060 3061 /* receive message of values*/ 3062 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3063 3064 /* insert into matrix */ 3065 jj = rstart; 3066 smycols = mycols; 3067 svals = vals; 3068 for (i=0; i<m; i++) { 3069 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3070 smycols += ourlens[i]; 3071 svals += ourlens[i]; 3072 jj++; 3073 } 3074 } 3075 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3076 ierr = PetscFree(vals);CHKERRQ(ierr); 3077 ierr = PetscFree(mycols);CHKERRQ(ierr); 3078 ierr = PetscFree(rowners);CHKERRQ(ierr); 3079 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3080 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3081 PetscFunctionReturn(0); 3082 } 3083 3084 #undef __FUNCT__ 3085 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3086 /* TODO: Not scalable because of ISAllGather(). */ 3087 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3088 { 3089 PetscErrorCode ierr; 3090 IS iscol_local; 3091 PetscInt csize; 3092 3093 PetscFunctionBegin; 3094 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3095 if (call == MAT_REUSE_MATRIX) { 3096 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3097 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3098 } else { 3099 PetscInt cbs; 3100 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3101 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3102 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3103 } 3104 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3105 if (call == MAT_INITIAL_MATRIX) { 3106 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3107 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3108 } 3109 PetscFunctionReturn(0); 3110 } 3111 3112 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3113 #undef __FUNCT__ 3114 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3115 /* 3116 Not great since it makes two copies of the submatrix, first an SeqAIJ 3117 in local and then by concatenating the local matrices the end result. 3118 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3119 3120 Note: This requires a sequential iscol with all indices. 3121 */ 3122 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3123 { 3124 PetscErrorCode ierr; 3125 PetscMPIInt rank,size; 3126 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3127 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3128 PetscBool allcolumns, colflag; 3129 Mat M,Mreuse; 3130 MatScalar *vwork,*aa; 3131 MPI_Comm comm; 3132 Mat_SeqAIJ *aij; 3133 3134 PetscFunctionBegin; 3135 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3136 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3137 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3138 3139 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3140 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3141 if (colflag && ncol == mat->cmap->N) { 3142 allcolumns = PETSC_TRUE; 3143 } else { 3144 allcolumns = PETSC_FALSE; 3145 } 3146 if (call == MAT_REUSE_MATRIX) { 3147 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3148 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3149 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3150 } else { 3151 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3152 } 3153 3154 /* 3155 m - number of local rows 3156 n - number of columns (same on all processors) 3157 rstart - first row in new global matrix generated 3158 */ 3159 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3160 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3161 if (call == MAT_INITIAL_MATRIX) { 3162 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3163 ii = aij->i; 3164 jj = aij->j; 3165 3166 /* 3167 Determine the number of non-zeros in the diagonal and off-diagonal 3168 portions of the matrix in order to do correct preallocation 3169 */ 3170 3171 /* first get start and end of "diagonal" columns */ 3172 if (csize == PETSC_DECIDE) { 3173 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3174 if (mglobal == n) { /* square matrix */ 3175 nlocal = m; 3176 } else { 3177 nlocal = n/size + ((n % size) > rank); 3178 } 3179 } else { 3180 nlocal = csize; 3181 } 3182 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3183 rstart = rend - nlocal; 3184 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3185 3186 /* next, compute all the lengths */ 3187 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3188 olens = dlens + m; 3189 for (i=0; i<m; i++) { 3190 jend = ii[i+1] - ii[i]; 3191 olen = 0; 3192 dlen = 0; 3193 for (j=0; j<jend; j++) { 3194 if (*jj < rstart || *jj >= rend) olen++; 3195 else dlen++; 3196 jj++; 3197 } 3198 olens[i] = olen; 3199 dlens[i] = dlen; 3200 } 3201 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3202 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3203 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3204 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3205 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3206 ierr = PetscFree(dlens);CHKERRQ(ierr); 3207 } else { 3208 PetscInt ml,nl; 3209 3210 M = *newmat; 3211 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3212 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3213 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3214 /* 3215 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3216 rather than the slower MatSetValues(). 3217 */ 3218 M->was_assembled = PETSC_TRUE; 3219 M->assembled = PETSC_FALSE; 3220 } 3221 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3222 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3223 ii = aij->i; 3224 jj = aij->j; 3225 aa = aij->a; 3226 for (i=0; i<m; i++) { 3227 row = rstart + i; 3228 nz = ii[i+1] - ii[i]; 3229 cwork = jj; jj += nz; 3230 vwork = aa; aa += nz; 3231 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3232 } 3233 3234 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3235 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3236 *newmat = M; 3237 3238 /* save submatrix used in processor for next request */ 3239 if (call == MAT_INITIAL_MATRIX) { 3240 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3241 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3242 } 3243 PetscFunctionReturn(0); 3244 } 3245 3246 #undef __FUNCT__ 3247 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3248 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3249 { 3250 PetscInt m,cstart, cend,j,nnz,i,d; 3251 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3252 const PetscInt *JJ; 3253 PetscScalar *values; 3254 PetscErrorCode ierr; 3255 3256 PetscFunctionBegin; 3257 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3258 3259 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3260 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3261 m = B->rmap->n; 3262 cstart = B->cmap->rstart; 3263 cend = B->cmap->rend; 3264 rstart = B->rmap->rstart; 3265 3266 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3267 3268 #if defined(PETSC_USE_DEBUGGING) 3269 for (i=0; i<m; i++) { 3270 nnz = Ii[i+1]- Ii[i]; 3271 JJ = J + Ii[i]; 3272 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3273 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3274 if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N); 3275 } 3276 #endif 3277 3278 for (i=0; i<m; i++) { 3279 nnz = Ii[i+1]- Ii[i]; 3280 JJ = J + Ii[i]; 3281 nnz_max = PetscMax(nnz_max,nnz); 3282 d = 0; 3283 for (j=0; j<nnz; j++) { 3284 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3285 } 3286 d_nnz[i] = d; 3287 o_nnz[i] = nnz - d; 3288 } 3289 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3290 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3291 3292 if (v) values = (PetscScalar*)v; 3293 else { 3294 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3295 } 3296 3297 for (i=0; i<m; i++) { 3298 ii = i + rstart; 3299 nnz = Ii[i+1]- Ii[i]; 3300 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3301 } 3302 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3303 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3304 3305 if (!v) { 3306 ierr = PetscFree(values);CHKERRQ(ierr); 3307 } 3308 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3309 PetscFunctionReturn(0); 3310 } 3311 3312 #undef __FUNCT__ 3313 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3314 /*@ 3315 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3316 (the default parallel PETSc format). 3317 3318 Collective on MPI_Comm 3319 3320 Input Parameters: 3321 + B - the matrix 3322 . i - the indices into j for the start of each local row (starts with zero) 3323 . j - the column indices for each local row (starts with zero) 3324 - v - optional values in the matrix 3325 3326 Level: developer 3327 3328 Notes: 3329 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3330 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3331 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3332 3333 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3334 3335 The format which is used for the sparse matrix input, is equivalent to a 3336 row-major ordering.. i.e for the following matrix, the input data expected is 3337 as shown: 3338 3339 1 0 0 3340 2 0 3 P0 3341 ------- 3342 4 5 6 P1 3343 3344 Process0 [P0]: rows_owned=[0,1] 3345 i = {0,1,3} [size = nrow+1 = 2+1] 3346 j = {0,0,2} [size = nz = 6] 3347 v = {1,2,3} [size = nz = 6] 3348 3349 Process1 [P1]: rows_owned=[2] 3350 i = {0,3} [size = nrow+1 = 1+1] 3351 j = {0,1,2} [size = nz = 6] 3352 v = {4,5,6} [size = nz = 6] 3353 3354 .keywords: matrix, aij, compressed row, sparse, parallel 3355 3356 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3357 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3358 @*/ 3359 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3360 { 3361 PetscErrorCode ierr; 3362 3363 PetscFunctionBegin; 3364 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3365 PetscFunctionReturn(0); 3366 } 3367 3368 #undef __FUNCT__ 3369 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3370 /*@C 3371 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3372 (the default parallel PETSc format). For good matrix assembly performance 3373 the user should preallocate the matrix storage by setting the parameters 3374 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3375 performance can be increased by more than a factor of 50. 3376 3377 Collective on MPI_Comm 3378 3379 Input Parameters: 3380 + B - the matrix 3381 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3382 (same value is used for all local rows) 3383 . d_nnz - array containing the number of nonzeros in the various rows of the 3384 DIAGONAL portion of the local submatrix (possibly different for each row) 3385 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3386 The size of this array is equal to the number of local rows, i.e 'm'. 3387 For matrices that will be factored, you must leave room for (and set) 3388 the diagonal entry even if it is zero. 3389 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3390 submatrix (same value is used for all local rows). 3391 - o_nnz - array containing the number of nonzeros in the various rows of the 3392 OFF-DIAGONAL portion of the local submatrix (possibly different for 3393 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3394 structure. The size of this array is equal to the number 3395 of local rows, i.e 'm'. 3396 3397 If the *_nnz parameter is given then the *_nz parameter is ignored 3398 3399 The AIJ format (also called the Yale sparse matrix format or 3400 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3401 storage. The stored row and column indices begin with zero. 3402 See Users-Manual: ch_mat for details. 3403 3404 The parallel matrix is partitioned such that the first m0 rows belong to 3405 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3406 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3407 3408 The DIAGONAL portion of the local submatrix of a processor can be defined 3409 as the submatrix which is obtained by extraction the part corresponding to 3410 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3411 first row that belongs to the processor, r2 is the last row belonging to 3412 the this processor, and c1-c2 is range of indices of the local part of a 3413 vector suitable for applying the matrix to. This is an mxn matrix. In the 3414 common case of a square matrix, the row and column ranges are the same and 3415 the DIAGONAL part is also square. The remaining portion of the local 3416 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3417 3418 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3419 3420 You can call MatGetInfo() to get information on how effective the preallocation was; 3421 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3422 You can also run with the option -info and look for messages with the string 3423 malloc in them to see if additional memory allocation was needed. 3424 3425 Example usage: 3426 3427 Consider the following 8x8 matrix with 34 non-zero values, that is 3428 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3429 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3430 as follows: 3431 3432 .vb 3433 1 2 0 | 0 3 0 | 0 4 3434 Proc0 0 5 6 | 7 0 0 | 8 0 3435 9 0 10 | 11 0 0 | 12 0 3436 ------------------------------------- 3437 13 0 14 | 15 16 17 | 0 0 3438 Proc1 0 18 0 | 19 20 21 | 0 0 3439 0 0 0 | 22 23 0 | 24 0 3440 ------------------------------------- 3441 Proc2 25 26 27 | 0 0 28 | 29 0 3442 30 0 0 | 31 32 33 | 0 34 3443 .ve 3444 3445 This can be represented as a collection of submatrices as: 3446 3447 .vb 3448 A B C 3449 D E F 3450 G H I 3451 .ve 3452 3453 Where the submatrices A,B,C are owned by proc0, D,E,F are 3454 owned by proc1, G,H,I are owned by proc2. 3455 3456 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3457 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3458 The 'M','N' parameters are 8,8, and have the same values on all procs. 3459 3460 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3461 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3462 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3463 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3464 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3465 matrix, ans [DF] as another SeqAIJ matrix. 3466 3467 When d_nz, o_nz parameters are specified, d_nz storage elements are 3468 allocated for every row of the local diagonal submatrix, and o_nz 3469 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3470 One way to choose d_nz and o_nz is to use the max nonzerors per local 3471 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3472 In this case, the values of d_nz,o_nz are: 3473 .vb 3474 proc0 : dnz = 2, o_nz = 2 3475 proc1 : dnz = 3, o_nz = 2 3476 proc2 : dnz = 1, o_nz = 4 3477 .ve 3478 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3479 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3480 for proc3. i.e we are using 12+15+10=37 storage locations to store 3481 34 values. 3482 3483 When d_nnz, o_nnz parameters are specified, the storage is specified 3484 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3485 In the above case the values for d_nnz,o_nnz are: 3486 .vb 3487 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3488 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3489 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3490 .ve 3491 Here the space allocated is sum of all the above values i.e 34, and 3492 hence pre-allocation is perfect. 3493 3494 Level: intermediate 3495 3496 .keywords: matrix, aij, compressed row, sparse, parallel 3497 3498 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3499 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3500 @*/ 3501 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3502 { 3503 PetscErrorCode ierr; 3504 3505 PetscFunctionBegin; 3506 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3507 PetscValidType(B,1); 3508 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3509 PetscFunctionReturn(0); 3510 } 3511 3512 #undef __FUNCT__ 3513 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3514 /*@ 3515 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3516 CSR format the local rows. 3517 3518 Collective on MPI_Comm 3519 3520 Input Parameters: 3521 + comm - MPI communicator 3522 . m - number of local rows (Cannot be PETSC_DECIDE) 3523 . n - This value should be the same as the local size used in creating the 3524 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3525 calculated if N is given) For square matrices n is almost always m. 3526 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3527 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3528 . i - row indices 3529 . j - column indices 3530 - a - matrix values 3531 3532 Output Parameter: 3533 . mat - the matrix 3534 3535 Level: intermediate 3536 3537 Notes: 3538 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3539 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3540 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3541 3542 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3543 3544 The format which is used for the sparse matrix input, is equivalent to a 3545 row-major ordering.. i.e for the following matrix, the input data expected is 3546 as shown: 3547 3548 1 0 0 3549 2 0 3 P0 3550 ------- 3551 4 5 6 P1 3552 3553 Process0 [P0]: rows_owned=[0,1] 3554 i = {0,1,3} [size = nrow+1 = 2+1] 3555 j = {0,0,2} [size = nz = 6] 3556 v = {1,2,3} [size = nz = 6] 3557 3558 Process1 [P1]: rows_owned=[2] 3559 i = {0,3} [size = nrow+1 = 1+1] 3560 j = {0,1,2} [size = nz = 6] 3561 v = {4,5,6} [size = nz = 6] 3562 3563 .keywords: matrix, aij, compressed row, sparse, parallel 3564 3565 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3566 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3567 @*/ 3568 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3569 { 3570 PetscErrorCode ierr; 3571 3572 PetscFunctionBegin; 3573 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3574 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3575 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3576 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3577 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3578 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3579 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3580 PetscFunctionReturn(0); 3581 } 3582 3583 #undef __FUNCT__ 3584 #define __FUNCT__ "MatCreateAIJ" 3585 /*@C 3586 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3587 (the default parallel PETSc format). For good matrix assembly performance 3588 the user should preallocate the matrix storage by setting the parameters 3589 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3590 performance can be increased by more than a factor of 50. 3591 3592 Collective on MPI_Comm 3593 3594 Input Parameters: 3595 + comm - MPI communicator 3596 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3597 This value should be the same as the local size used in creating the 3598 y vector for the matrix-vector product y = Ax. 3599 . n - This value should be the same as the local size used in creating the 3600 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3601 calculated if N is given) For square matrices n is almost always m. 3602 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3603 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3604 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3605 (same value is used for all local rows) 3606 . d_nnz - array containing the number of nonzeros in the various rows of the 3607 DIAGONAL portion of the local submatrix (possibly different for each row) 3608 or NULL, if d_nz is used to specify the nonzero structure. 3609 The size of this array is equal to the number of local rows, i.e 'm'. 3610 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3611 submatrix (same value is used for all local rows). 3612 - o_nnz - array containing the number of nonzeros in the various rows of the 3613 OFF-DIAGONAL portion of the local submatrix (possibly different for 3614 each row) or NULL, if o_nz is used to specify the nonzero 3615 structure. The size of this array is equal to the number 3616 of local rows, i.e 'm'. 3617 3618 Output Parameter: 3619 . A - the matrix 3620 3621 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3622 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3623 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3624 3625 Notes: 3626 If the *_nnz parameter is given then the *_nz parameter is ignored 3627 3628 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3629 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3630 storage requirements for this matrix. 3631 3632 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3633 processor than it must be used on all processors that share the object for 3634 that argument. 3635 3636 The user MUST specify either the local or global matrix dimensions 3637 (possibly both). 3638 3639 The parallel matrix is partitioned across processors such that the 3640 first m0 rows belong to process 0, the next m1 rows belong to 3641 process 1, the next m2 rows belong to process 2 etc.. where 3642 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3643 values corresponding to [m x N] submatrix. 3644 3645 The columns are logically partitioned with the n0 columns belonging 3646 to 0th partition, the next n1 columns belonging to the next 3647 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3648 3649 The DIAGONAL portion of the local submatrix on any given processor 3650 is the submatrix corresponding to the rows and columns m,n 3651 corresponding to the given processor. i.e diagonal matrix on 3652 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3653 etc. The remaining portion of the local submatrix [m x (N-n)] 3654 constitute the OFF-DIAGONAL portion. The example below better 3655 illustrates this concept. 3656 3657 For a square global matrix we define each processor's diagonal portion 3658 to be its local rows and the corresponding columns (a square submatrix); 3659 each processor's off-diagonal portion encompasses the remainder of the 3660 local matrix (a rectangular submatrix). 3661 3662 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3663 3664 When calling this routine with a single process communicator, a matrix of 3665 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3666 type of communicator, use the construction mechanism: 3667 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3668 3669 By default, this format uses inodes (identical nodes) when possible. 3670 We search for consecutive rows with the same nonzero structure, thereby 3671 reusing matrix information to achieve increased efficiency. 3672 3673 Options Database Keys: 3674 + -mat_no_inode - Do not use inodes 3675 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3676 - -mat_aij_oneindex - Internally use indexing starting at 1 3677 rather than 0. Note that when calling MatSetValues(), 3678 the user still MUST index entries starting at 0! 3679 3680 3681 Example usage: 3682 3683 Consider the following 8x8 matrix with 34 non-zero values, that is 3684 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3685 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3686 as follows: 3687 3688 .vb 3689 1 2 0 | 0 3 0 | 0 4 3690 Proc0 0 5 6 | 7 0 0 | 8 0 3691 9 0 10 | 11 0 0 | 12 0 3692 ------------------------------------- 3693 13 0 14 | 15 16 17 | 0 0 3694 Proc1 0 18 0 | 19 20 21 | 0 0 3695 0 0 0 | 22 23 0 | 24 0 3696 ------------------------------------- 3697 Proc2 25 26 27 | 0 0 28 | 29 0 3698 30 0 0 | 31 32 33 | 0 34 3699 .ve 3700 3701 This can be represented as a collection of submatrices as: 3702 3703 .vb 3704 A B C 3705 D E F 3706 G H I 3707 .ve 3708 3709 Where the submatrices A,B,C are owned by proc0, D,E,F are 3710 owned by proc1, G,H,I are owned by proc2. 3711 3712 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3713 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3714 The 'M','N' parameters are 8,8, and have the same values on all procs. 3715 3716 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3717 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3718 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3719 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3720 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3721 matrix, ans [DF] as another SeqAIJ matrix. 3722 3723 When d_nz, o_nz parameters are specified, d_nz storage elements are 3724 allocated for every row of the local diagonal submatrix, and o_nz 3725 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3726 One way to choose d_nz and o_nz is to use the max nonzerors per local 3727 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3728 In this case, the values of d_nz,o_nz are: 3729 .vb 3730 proc0 : dnz = 2, o_nz = 2 3731 proc1 : dnz = 3, o_nz = 2 3732 proc2 : dnz = 1, o_nz = 4 3733 .ve 3734 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3735 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3736 for proc3. i.e we are using 12+15+10=37 storage locations to store 3737 34 values. 3738 3739 When d_nnz, o_nnz parameters are specified, the storage is specified 3740 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3741 In the above case the values for d_nnz,o_nnz are: 3742 .vb 3743 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3744 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3745 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3746 .ve 3747 Here the space allocated is sum of all the above values i.e 34, and 3748 hence pre-allocation is perfect. 3749 3750 Level: intermediate 3751 3752 .keywords: matrix, aij, compressed row, sparse, parallel 3753 3754 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3755 MPIAIJ, MatCreateMPIAIJWithArrays() 3756 @*/ 3757 PetscErrorCode MatCreateAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3758 { 3759 PetscErrorCode ierr; 3760 PetscMPIInt size; 3761 3762 PetscFunctionBegin; 3763 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3764 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3765 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3766 if (size > 1) { 3767 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3768 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3769 } else { 3770 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3771 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3772 } 3773 PetscFunctionReturn(0); 3774 } 3775 3776 #undef __FUNCT__ 3777 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3778 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3779 { 3780 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3781 3782 PetscFunctionBegin; 3783 if (Ad) *Ad = a->A; 3784 if (Ao) *Ao = a->B; 3785 if (colmap) *colmap = a->garray; 3786 PetscFunctionReturn(0); 3787 } 3788 3789 #undef __FUNCT__ 3790 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3791 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3792 { 3793 PetscErrorCode ierr; 3794 PetscInt i; 3795 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3796 3797 PetscFunctionBegin; 3798 if (coloring->ctype == IS_COLORING_GLOBAL) { 3799 ISColoringValue *allcolors,*colors; 3800 ISColoring ocoloring; 3801 3802 /* set coloring for diagonal portion */ 3803 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3804 3805 /* set coloring for off-diagonal portion */ 3806 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3807 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3808 for (i=0; i<a->B->cmap->n; i++) { 3809 colors[i] = allcolors[a->garray[i]]; 3810 } 3811 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3812 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3813 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3814 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3815 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3816 ISColoringValue *colors; 3817 PetscInt *larray; 3818 ISColoring ocoloring; 3819 3820 /* set coloring for diagonal portion */ 3821 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3822 for (i=0; i<a->A->cmap->n; i++) { 3823 larray[i] = i + A->cmap->rstart; 3824 } 3825 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3826 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3827 for (i=0; i<a->A->cmap->n; i++) { 3828 colors[i] = coloring->colors[larray[i]]; 3829 } 3830 ierr = PetscFree(larray);CHKERRQ(ierr); 3831 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3832 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3833 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3834 3835 /* set coloring for off-diagonal portion */ 3836 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3837 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3838 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3839 for (i=0; i<a->B->cmap->n; i++) { 3840 colors[i] = coloring->colors[larray[i]]; 3841 } 3842 ierr = PetscFree(larray);CHKERRQ(ierr); 3843 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3844 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3845 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3846 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3847 PetscFunctionReturn(0); 3848 } 3849 3850 #undef __FUNCT__ 3851 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3852 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3853 { 3854 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3855 PetscErrorCode ierr; 3856 3857 PetscFunctionBegin; 3858 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3859 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3860 PetscFunctionReturn(0); 3861 } 3862 3863 #undef __FUNCT__ 3864 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3865 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3866 { 3867 PetscErrorCode ierr; 3868 PetscInt m,N,i,rstart,nnz,Ii; 3869 PetscInt *indx; 3870 PetscScalar *values; 3871 3872 PetscFunctionBegin; 3873 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3874 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3875 PetscInt *dnz,*onz,sum,bs,cbs; 3876 3877 if (n == PETSC_DECIDE) { 3878 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3879 } 3880 /* Check sum(n) = N */ 3881 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3882 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3883 3884 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3885 rstart -= m; 3886 3887 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3888 for (i=0; i<m; i++) { 3889 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3890 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3891 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3892 } 3893 3894 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3895 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3896 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3897 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3898 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3899 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3900 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3901 } 3902 3903 /* numeric phase */ 3904 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3905 for (i=0; i<m; i++) { 3906 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3907 Ii = i + rstart; 3908 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3909 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3910 } 3911 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3912 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3913 PetscFunctionReturn(0); 3914 } 3915 3916 #undef __FUNCT__ 3917 #define __FUNCT__ "MatFileSplit" 3918 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3919 { 3920 PetscErrorCode ierr; 3921 PetscMPIInt rank; 3922 PetscInt m,N,i,rstart,nnz; 3923 size_t len; 3924 const PetscInt *indx; 3925 PetscViewer out; 3926 char *name; 3927 Mat B; 3928 const PetscScalar *values; 3929 3930 PetscFunctionBegin; 3931 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3932 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3933 /* Should this be the type of the diagonal block of A? */ 3934 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3935 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3936 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3937 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3938 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3939 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3940 for (i=0; i<m; i++) { 3941 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3942 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3943 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3944 } 3945 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3946 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3947 3948 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3949 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3950 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3951 sprintf(name,"%s.%d",outfile,rank); 3952 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3953 ierr = PetscFree(name);CHKERRQ(ierr); 3954 ierr = MatView(B,out);CHKERRQ(ierr); 3955 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3956 ierr = MatDestroy(&B);CHKERRQ(ierr); 3957 PetscFunctionReturn(0); 3958 } 3959 3960 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3961 #undef __FUNCT__ 3962 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3963 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3964 { 3965 PetscErrorCode ierr; 3966 Mat_Merge_SeqsToMPI *merge; 3967 PetscContainer container; 3968 3969 PetscFunctionBegin; 3970 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3971 if (container) { 3972 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3973 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3974 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3975 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3976 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3977 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3978 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3979 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3980 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3981 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3982 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3983 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3984 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3985 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3986 ierr = PetscFree(merge);CHKERRQ(ierr); 3987 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3988 } 3989 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3990 PetscFunctionReturn(0); 3991 } 3992 3993 #include <../src/mat/utils/freespace.h> 3994 #include <petscbt.h> 3995 3996 #undef __FUNCT__ 3997 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 3998 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 3999 { 4000 PetscErrorCode ierr; 4001 MPI_Comm comm; 4002 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4003 PetscMPIInt size,rank,taga,*len_s; 4004 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4005 PetscInt proc,m; 4006 PetscInt **buf_ri,**buf_rj; 4007 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4008 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4009 MPI_Request *s_waits,*r_waits; 4010 MPI_Status *status; 4011 MatScalar *aa=a->a; 4012 MatScalar **abuf_r,*ba_i; 4013 Mat_Merge_SeqsToMPI *merge; 4014 PetscContainer container; 4015 4016 PetscFunctionBegin; 4017 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4018 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4019 4020 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4021 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4022 4023 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4024 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4025 4026 bi = merge->bi; 4027 bj = merge->bj; 4028 buf_ri = merge->buf_ri; 4029 buf_rj = merge->buf_rj; 4030 4031 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4032 owners = merge->rowmap->range; 4033 len_s = merge->len_s; 4034 4035 /* send and recv matrix values */ 4036 /*-----------------------------*/ 4037 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4038 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4039 4040 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4041 for (proc=0,k=0; proc<size; proc++) { 4042 if (!len_s[proc]) continue; 4043 i = owners[proc]; 4044 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4045 k++; 4046 } 4047 4048 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4049 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4050 ierr = PetscFree(status);CHKERRQ(ierr); 4051 4052 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4053 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4054 4055 /* insert mat values of mpimat */ 4056 /*----------------------------*/ 4057 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4058 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4059 4060 for (k=0; k<merge->nrecv; k++) { 4061 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4062 nrows = *(buf_ri_k[k]); 4063 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4064 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4065 } 4066 4067 /* set values of ba */ 4068 m = merge->rowmap->n; 4069 for (i=0; i<m; i++) { 4070 arow = owners[rank] + i; 4071 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4072 bnzi = bi[i+1] - bi[i]; 4073 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4074 4075 /* add local non-zero vals of this proc's seqmat into ba */ 4076 anzi = ai[arow+1] - ai[arow]; 4077 aj = a->j + ai[arow]; 4078 aa = a->a + ai[arow]; 4079 nextaj = 0; 4080 for (j=0; nextaj<anzi; j++) { 4081 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4082 ba_i[j] += aa[nextaj++]; 4083 } 4084 } 4085 4086 /* add received vals into ba */ 4087 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4088 /* i-th row */ 4089 if (i == *nextrow[k]) { 4090 anzi = *(nextai[k]+1) - *nextai[k]; 4091 aj = buf_rj[k] + *(nextai[k]); 4092 aa = abuf_r[k] + *(nextai[k]); 4093 nextaj = 0; 4094 for (j=0; nextaj<anzi; j++) { 4095 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4096 ba_i[j] += aa[nextaj++]; 4097 } 4098 } 4099 nextrow[k]++; nextai[k]++; 4100 } 4101 } 4102 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4103 } 4104 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4105 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4106 4107 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4108 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4109 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4110 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4111 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4112 PetscFunctionReturn(0); 4113 } 4114 4115 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4116 4117 #undef __FUNCT__ 4118 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4119 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4120 { 4121 PetscErrorCode ierr; 4122 Mat B_mpi; 4123 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4124 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4125 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4126 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4127 PetscInt len,proc,*dnz,*onz,bs,cbs; 4128 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4129 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4130 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4131 MPI_Status *status; 4132 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4133 PetscBT lnkbt; 4134 Mat_Merge_SeqsToMPI *merge; 4135 PetscContainer container; 4136 4137 PetscFunctionBegin; 4138 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4139 4140 /* make sure it is a PETSc comm */ 4141 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4142 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4143 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4144 4145 ierr = PetscNew(&merge);CHKERRQ(ierr); 4146 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4147 4148 /* determine row ownership */ 4149 /*---------------------------------------------------------*/ 4150 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4151 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4152 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4153 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4154 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4155 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4156 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4157 4158 m = merge->rowmap->n; 4159 owners = merge->rowmap->range; 4160 4161 /* determine the number of messages to send, their lengths */ 4162 /*---------------------------------------------------------*/ 4163 len_s = merge->len_s; 4164 4165 len = 0; /* length of buf_si[] */ 4166 merge->nsend = 0; 4167 for (proc=0; proc<size; proc++) { 4168 len_si[proc] = 0; 4169 if (proc == rank) { 4170 len_s[proc] = 0; 4171 } else { 4172 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4173 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4174 } 4175 if (len_s[proc]) { 4176 merge->nsend++; 4177 nrows = 0; 4178 for (i=owners[proc]; i<owners[proc+1]; i++) { 4179 if (ai[i+1] > ai[i]) nrows++; 4180 } 4181 len_si[proc] = 2*(nrows+1); 4182 len += len_si[proc]; 4183 } 4184 } 4185 4186 /* determine the number and length of messages to receive for ij-structure */ 4187 /*-------------------------------------------------------------------------*/ 4188 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4189 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4190 4191 /* post the Irecv of j-structure */ 4192 /*-------------------------------*/ 4193 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4194 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4195 4196 /* post the Isend of j-structure */ 4197 /*--------------------------------*/ 4198 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4199 4200 for (proc=0, k=0; proc<size; proc++) { 4201 if (!len_s[proc]) continue; 4202 i = owners[proc]; 4203 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4204 k++; 4205 } 4206 4207 /* receives and sends of j-structure are complete */ 4208 /*------------------------------------------------*/ 4209 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4210 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4211 4212 /* send and recv i-structure */ 4213 /*---------------------------*/ 4214 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4215 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4216 4217 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4218 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4219 for (proc=0,k=0; proc<size; proc++) { 4220 if (!len_s[proc]) continue; 4221 /* form outgoing message for i-structure: 4222 buf_si[0]: nrows to be sent 4223 [1:nrows]: row index (global) 4224 [nrows+1:2*nrows+1]: i-structure index 4225 */ 4226 /*-------------------------------------------*/ 4227 nrows = len_si[proc]/2 - 1; 4228 buf_si_i = buf_si + nrows+1; 4229 buf_si[0] = nrows; 4230 buf_si_i[0] = 0; 4231 nrows = 0; 4232 for (i=owners[proc]; i<owners[proc+1]; i++) { 4233 anzi = ai[i+1] - ai[i]; 4234 if (anzi) { 4235 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4236 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4237 nrows++; 4238 } 4239 } 4240 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4241 k++; 4242 buf_si += len_si[proc]; 4243 } 4244 4245 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4246 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4247 4248 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4249 for (i=0; i<merge->nrecv; i++) { 4250 ierr = PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);CHKERRQ(ierr); 4251 } 4252 4253 ierr = PetscFree(len_si);CHKERRQ(ierr); 4254 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4255 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4256 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4257 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4258 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4259 ierr = PetscFree(status);CHKERRQ(ierr); 4260 4261 /* compute a local seq matrix in each processor */ 4262 /*----------------------------------------------*/ 4263 /* allocate bi array and free space for accumulating nonzero column info */ 4264 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4265 bi[0] = 0; 4266 4267 /* create and initialize a linked list */ 4268 nlnk = N+1; 4269 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4270 4271 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4272 len = ai[owners[rank+1]] - ai[owners[rank]]; 4273 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4274 4275 current_space = free_space; 4276 4277 /* determine symbolic info for each local row */ 4278 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4279 4280 for (k=0; k<merge->nrecv; k++) { 4281 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4282 nrows = *buf_ri_k[k]; 4283 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4284 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4285 } 4286 4287 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4288 len = 0; 4289 for (i=0; i<m; i++) { 4290 bnzi = 0; 4291 /* add local non-zero cols of this proc's seqmat into lnk */ 4292 arow = owners[rank] + i; 4293 anzi = ai[arow+1] - ai[arow]; 4294 aj = a->j + ai[arow]; 4295 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4296 bnzi += nlnk; 4297 /* add received col data into lnk */ 4298 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4299 if (i == *nextrow[k]) { /* i-th row */ 4300 anzi = *(nextai[k]+1) - *nextai[k]; 4301 aj = buf_rj[k] + *nextai[k]; 4302 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4303 bnzi += nlnk; 4304 nextrow[k]++; nextai[k]++; 4305 } 4306 } 4307 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4308 4309 /* if free space is not available, make more free space */ 4310 if (current_space->local_remaining<bnzi) { 4311 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4312 nspacedouble++; 4313 } 4314 /* copy data into free space, then initialize lnk */ 4315 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4316 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4317 4318 current_space->array += bnzi; 4319 current_space->local_used += bnzi; 4320 current_space->local_remaining -= bnzi; 4321 4322 bi[i+1] = bi[i] + bnzi; 4323 } 4324 4325 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4326 4327 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4328 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4329 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4330 4331 /* create symbolic parallel matrix B_mpi */ 4332 /*---------------------------------------*/ 4333 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4334 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4335 if (n==PETSC_DECIDE) { 4336 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4337 } else { 4338 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4339 } 4340 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4341 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4342 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4343 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4344 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4345 4346 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4347 B_mpi->assembled = PETSC_FALSE; 4348 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4349 merge->bi = bi; 4350 merge->bj = bj; 4351 merge->buf_ri = buf_ri; 4352 merge->buf_rj = buf_rj; 4353 merge->coi = NULL; 4354 merge->coj = NULL; 4355 merge->owners_co = NULL; 4356 4357 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4358 4359 /* attach the supporting struct to B_mpi for reuse */ 4360 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4361 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4362 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4363 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4364 *mpimat = B_mpi; 4365 4366 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4367 PetscFunctionReturn(0); 4368 } 4369 4370 #undef __FUNCT__ 4371 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4372 /*@C 4373 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4374 matrices from each processor 4375 4376 Collective on MPI_Comm 4377 4378 Input Parameters: 4379 + comm - the communicators the parallel matrix will live on 4380 . seqmat - the input sequential matrices 4381 . m - number of local rows (or PETSC_DECIDE) 4382 . n - number of local columns (or PETSC_DECIDE) 4383 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4384 4385 Output Parameter: 4386 . mpimat - the parallel matrix generated 4387 4388 Level: advanced 4389 4390 Notes: 4391 The dimensions of the sequential matrix in each processor MUST be the same. 4392 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4393 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4394 @*/ 4395 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4396 { 4397 PetscErrorCode ierr; 4398 PetscMPIInt size; 4399 4400 PetscFunctionBegin; 4401 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4402 if (size == 1) { 4403 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4404 if (scall == MAT_INITIAL_MATRIX) { 4405 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4406 } else { 4407 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4408 } 4409 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4410 PetscFunctionReturn(0); 4411 } 4412 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4413 if (scall == MAT_INITIAL_MATRIX) { 4414 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4415 } 4416 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4417 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4418 PetscFunctionReturn(0); 4419 } 4420 4421 #undef __FUNCT__ 4422 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4423 /*@ 4424 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4425 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4426 with MatGetSize() 4427 4428 Not Collective 4429 4430 Input Parameters: 4431 + A - the matrix 4432 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4433 4434 Output Parameter: 4435 . A_loc - the local sequential matrix generated 4436 4437 Level: developer 4438 4439 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4440 4441 @*/ 4442 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4443 { 4444 PetscErrorCode ierr; 4445 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4446 Mat_SeqAIJ *mat,*a,*b; 4447 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4448 MatScalar *aa,*ba,*cam; 4449 PetscScalar *ca; 4450 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4451 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4452 PetscBool match; 4453 MPI_Comm comm; 4454 PetscMPIInt size; 4455 4456 PetscFunctionBegin; 4457 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4458 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4459 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4460 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4461 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4462 4463 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4464 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4465 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4466 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4467 aa = a->a; ba = b->a; 4468 if (scall == MAT_INITIAL_MATRIX) { 4469 if (size == 1) { 4470 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4471 PetscFunctionReturn(0); 4472 } 4473 4474 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4475 ci[0] = 0; 4476 for (i=0; i<am; i++) { 4477 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4478 } 4479 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4480 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4481 k = 0; 4482 for (i=0; i<am; i++) { 4483 ncols_o = bi[i+1] - bi[i]; 4484 ncols_d = ai[i+1] - ai[i]; 4485 /* off-diagonal portion of A */ 4486 for (jo=0; jo<ncols_o; jo++) { 4487 col = cmap[*bj]; 4488 if (col >= cstart) break; 4489 cj[k] = col; bj++; 4490 ca[k++] = *ba++; 4491 } 4492 /* diagonal portion of A */ 4493 for (j=0; j<ncols_d; j++) { 4494 cj[k] = cstart + *aj++; 4495 ca[k++] = *aa++; 4496 } 4497 /* off-diagonal portion of A */ 4498 for (j=jo; j<ncols_o; j++) { 4499 cj[k] = cmap[*bj++]; 4500 ca[k++] = *ba++; 4501 } 4502 } 4503 /* put together the new matrix */ 4504 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4505 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4506 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4507 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4508 mat->free_a = PETSC_TRUE; 4509 mat->free_ij = PETSC_TRUE; 4510 mat->nonew = 0; 4511 } else if (scall == MAT_REUSE_MATRIX) { 4512 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4513 ci = mat->i; cj = mat->j; cam = mat->a; 4514 for (i=0; i<am; i++) { 4515 /* off-diagonal portion of A */ 4516 ncols_o = bi[i+1] - bi[i]; 4517 for (jo=0; jo<ncols_o; jo++) { 4518 col = cmap[*bj]; 4519 if (col >= cstart) break; 4520 *cam++ = *ba++; bj++; 4521 } 4522 /* diagonal portion of A */ 4523 ncols_d = ai[i+1] - ai[i]; 4524 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4525 /* off-diagonal portion of A */ 4526 for (j=jo; j<ncols_o; j++) { 4527 *cam++ = *ba++; bj++; 4528 } 4529 } 4530 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4531 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4532 PetscFunctionReturn(0); 4533 } 4534 4535 #undef __FUNCT__ 4536 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4537 /*@C 4538 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4539 4540 Not Collective 4541 4542 Input Parameters: 4543 + A - the matrix 4544 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4545 - row, col - index sets of rows and columns to extract (or NULL) 4546 4547 Output Parameter: 4548 . A_loc - the local sequential matrix generated 4549 4550 Level: developer 4551 4552 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4553 4554 @*/ 4555 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4556 { 4557 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4558 PetscErrorCode ierr; 4559 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4560 IS isrowa,iscola; 4561 Mat *aloc; 4562 PetscBool match; 4563 4564 PetscFunctionBegin; 4565 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4566 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4567 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4568 if (!row) { 4569 start = A->rmap->rstart; end = A->rmap->rend; 4570 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4571 } else { 4572 isrowa = *row; 4573 } 4574 if (!col) { 4575 start = A->cmap->rstart; 4576 cmap = a->garray; 4577 nzA = a->A->cmap->n; 4578 nzB = a->B->cmap->n; 4579 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4580 ncols = 0; 4581 for (i=0; i<nzB; i++) { 4582 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4583 else break; 4584 } 4585 imark = i; 4586 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4587 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4588 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4589 } else { 4590 iscola = *col; 4591 } 4592 if (scall != MAT_INITIAL_MATRIX) { 4593 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4594 aloc[0] = *A_loc; 4595 } 4596 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4597 *A_loc = aloc[0]; 4598 ierr = PetscFree(aloc);CHKERRQ(ierr); 4599 if (!row) { 4600 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4601 } 4602 if (!col) { 4603 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4604 } 4605 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4606 PetscFunctionReturn(0); 4607 } 4608 4609 #undef __FUNCT__ 4610 #define __FUNCT__ "MatGetBrowsOfAcols" 4611 /*@C 4612 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4613 4614 Collective on Mat 4615 4616 Input Parameters: 4617 + A,B - the matrices in mpiaij format 4618 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4619 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4620 4621 Output Parameter: 4622 + rowb, colb - index sets of rows and columns of B to extract 4623 - B_seq - the sequential matrix generated 4624 4625 Level: developer 4626 4627 @*/ 4628 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4629 { 4630 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4631 PetscErrorCode ierr; 4632 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4633 IS isrowb,iscolb; 4634 Mat *bseq=NULL; 4635 4636 PetscFunctionBegin; 4637 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4638 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4639 } 4640 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4641 4642 if (scall == MAT_INITIAL_MATRIX) { 4643 start = A->cmap->rstart; 4644 cmap = a->garray; 4645 nzA = a->A->cmap->n; 4646 nzB = a->B->cmap->n; 4647 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4648 ncols = 0; 4649 for (i=0; i<nzB; i++) { /* row < local row index */ 4650 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4651 else break; 4652 } 4653 imark = i; 4654 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4655 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4656 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4657 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4658 } else { 4659 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4660 isrowb = *rowb; iscolb = *colb; 4661 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4662 bseq[0] = *B_seq; 4663 } 4664 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4665 *B_seq = bseq[0]; 4666 ierr = PetscFree(bseq);CHKERRQ(ierr); 4667 if (!rowb) { 4668 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4669 } else { 4670 *rowb = isrowb; 4671 } 4672 if (!colb) { 4673 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4674 } else { 4675 *colb = iscolb; 4676 } 4677 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4678 PetscFunctionReturn(0); 4679 } 4680 4681 #undef __FUNCT__ 4682 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4683 /* 4684 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4685 of the OFF-DIAGONAL portion of local A 4686 4687 Collective on Mat 4688 4689 Input Parameters: 4690 + A,B - the matrices in mpiaij format 4691 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4692 4693 Output Parameter: 4694 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4695 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4696 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4697 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4698 4699 Level: developer 4700 4701 */ 4702 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4703 { 4704 VecScatter_MPI_General *gen_to,*gen_from; 4705 PetscErrorCode ierr; 4706 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4707 Mat_SeqAIJ *b_oth; 4708 VecScatter ctx =a->Mvctx; 4709 MPI_Comm comm; 4710 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4711 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4712 PetscScalar *rvalues,*svalues; 4713 MatScalar *b_otha,*bufa,*bufA; 4714 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4715 MPI_Request *rwaits = NULL,*swaits = NULL; 4716 MPI_Status *sstatus,rstatus; 4717 PetscMPIInt jj,size; 4718 PetscInt *cols,sbs,rbs; 4719 PetscScalar *vals; 4720 4721 PetscFunctionBegin; 4722 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4723 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4724 4725 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4726 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4727 } 4728 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4729 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4730 4731 gen_to = (VecScatter_MPI_General*)ctx->todata; 4732 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4733 rvalues = gen_from->values; /* holds the length of receiving row */ 4734 svalues = gen_to->values; /* holds the length of sending row */ 4735 nrecvs = gen_from->n; 4736 nsends = gen_to->n; 4737 4738 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4739 srow = gen_to->indices; /* local row index to be sent */ 4740 sstarts = gen_to->starts; 4741 sprocs = gen_to->procs; 4742 sstatus = gen_to->sstatus; 4743 sbs = gen_to->bs; 4744 rstarts = gen_from->starts; 4745 rprocs = gen_from->procs; 4746 rbs = gen_from->bs; 4747 4748 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4749 if (scall == MAT_INITIAL_MATRIX) { 4750 /* i-array */ 4751 /*---------*/ 4752 /* post receives */ 4753 for (i=0; i<nrecvs; i++) { 4754 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4755 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4756 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4757 } 4758 4759 /* pack the outgoing message */ 4760 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4761 4762 sstartsj[0] = 0; 4763 rstartsj[0] = 0; 4764 len = 0; /* total length of j or a array to be sent */ 4765 k = 0; 4766 for (i=0; i<nsends; i++) { 4767 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4768 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4769 for (j=0; j<nrows; j++) { 4770 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4771 for (l=0; l<sbs; l++) { 4772 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4773 4774 rowlen[j*sbs+l] = ncols; 4775 4776 len += ncols; 4777 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4778 } 4779 k++; 4780 } 4781 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4782 4783 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4784 } 4785 /* recvs and sends of i-array are completed */ 4786 i = nrecvs; 4787 while (i--) { 4788 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4789 } 4790 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4791 4792 /* allocate buffers for sending j and a arrays */ 4793 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4794 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4795 4796 /* create i-array of B_oth */ 4797 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4798 4799 b_othi[0] = 0; 4800 len = 0; /* total length of j or a array to be received */ 4801 k = 0; 4802 for (i=0; i<nrecvs; i++) { 4803 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4804 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4805 for (j=0; j<nrows; j++) { 4806 b_othi[k+1] = b_othi[k] + rowlen[j]; 4807 len += rowlen[j]; k++; 4808 } 4809 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4810 } 4811 4812 /* allocate space for j and a arrrays of B_oth */ 4813 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4814 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4815 4816 /* j-array */ 4817 /*---------*/ 4818 /* post receives of j-array */ 4819 for (i=0; i<nrecvs; i++) { 4820 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4821 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4822 } 4823 4824 /* pack the outgoing message j-array */ 4825 k = 0; 4826 for (i=0; i<nsends; i++) { 4827 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4828 bufJ = bufj+sstartsj[i]; 4829 for (j=0; j<nrows; j++) { 4830 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4831 for (ll=0; ll<sbs; ll++) { 4832 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4833 for (l=0; l<ncols; l++) { 4834 *bufJ++ = cols[l]; 4835 } 4836 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4837 } 4838 } 4839 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4840 } 4841 4842 /* recvs and sends of j-array are completed */ 4843 i = nrecvs; 4844 while (i--) { 4845 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4846 } 4847 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4848 } else if (scall == MAT_REUSE_MATRIX) { 4849 sstartsj = *startsj_s; 4850 rstartsj = *startsj_r; 4851 bufa = *bufa_ptr; 4852 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4853 b_otha = b_oth->a; 4854 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4855 4856 /* a-array */ 4857 /*---------*/ 4858 /* post receives of a-array */ 4859 for (i=0; i<nrecvs; i++) { 4860 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4861 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4862 } 4863 4864 /* pack the outgoing message a-array */ 4865 k = 0; 4866 for (i=0; i<nsends; i++) { 4867 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4868 bufA = bufa+sstartsj[i]; 4869 for (j=0; j<nrows; j++) { 4870 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4871 for (ll=0; ll<sbs; ll++) { 4872 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4873 for (l=0; l<ncols; l++) { 4874 *bufA++ = vals[l]; 4875 } 4876 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4877 } 4878 } 4879 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4880 } 4881 /* recvs and sends of a-array are completed */ 4882 i = nrecvs; 4883 while (i--) { 4884 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4885 } 4886 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4887 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4888 4889 if (scall == MAT_INITIAL_MATRIX) { 4890 /* put together the new matrix */ 4891 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4892 4893 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4894 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4895 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4896 b_oth->free_a = PETSC_TRUE; 4897 b_oth->free_ij = PETSC_TRUE; 4898 b_oth->nonew = 0; 4899 4900 ierr = PetscFree(bufj);CHKERRQ(ierr); 4901 if (!startsj_s || !bufa_ptr) { 4902 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4903 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4904 } else { 4905 *startsj_s = sstartsj; 4906 *startsj_r = rstartsj; 4907 *bufa_ptr = bufa; 4908 } 4909 } 4910 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4911 PetscFunctionReturn(0); 4912 } 4913 4914 #undef __FUNCT__ 4915 #define __FUNCT__ "MatGetCommunicationStructs" 4916 /*@C 4917 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4918 4919 Not Collective 4920 4921 Input Parameters: 4922 . A - The matrix in mpiaij format 4923 4924 Output Parameter: 4925 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4926 . colmap - A map from global column index to local index into lvec 4927 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4928 4929 Level: developer 4930 4931 @*/ 4932 #if defined(PETSC_USE_CTABLE) 4933 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4934 #else 4935 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4936 #endif 4937 { 4938 Mat_MPIAIJ *a; 4939 4940 PetscFunctionBegin; 4941 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4942 PetscValidPointer(lvec, 2); 4943 PetscValidPointer(colmap, 3); 4944 PetscValidPointer(multScatter, 4); 4945 a = (Mat_MPIAIJ*) A->data; 4946 if (lvec) *lvec = a->lvec; 4947 if (colmap) *colmap = a->colmap; 4948 if (multScatter) *multScatter = a->Mvctx; 4949 PetscFunctionReturn(0); 4950 } 4951 4952 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4953 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4954 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4955 #if defined(PETSC_HAVE_ELEMENTAL) 4956 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4957 #endif 4958 4959 #undef __FUNCT__ 4960 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4961 /* 4962 Computes (B'*A')' since computing B*A directly is untenable 4963 4964 n p p 4965 ( ) ( ) ( ) 4966 m ( A ) * n ( B ) = m ( C ) 4967 ( ) ( ) ( ) 4968 4969 */ 4970 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4971 { 4972 PetscErrorCode ierr; 4973 Mat At,Bt,Ct; 4974 4975 PetscFunctionBegin; 4976 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4977 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4978 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4979 ierr = MatDestroy(&At);CHKERRQ(ierr); 4980 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4981 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4982 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4983 PetscFunctionReturn(0); 4984 } 4985 4986 #undef __FUNCT__ 4987 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4988 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4989 { 4990 PetscErrorCode ierr; 4991 PetscInt m=A->rmap->n,n=B->cmap->n; 4992 Mat Cmat; 4993 4994 PetscFunctionBegin; 4995 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 4996 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4997 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4998 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4999 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5000 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5001 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5002 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5003 5004 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5005 5006 *C = Cmat; 5007 PetscFunctionReturn(0); 5008 } 5009 5010 /* ----------------------------------------------------------------*/ 5011 #undef __FUNCT__ 5012 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5013 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5014 { 5015 PetscErrorCode ierr; 5016 5017 PetscFunctionBegin; 5018 if (scall == MAT_INITIAL_MATRIX) { 5019 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5020 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5021 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5022 } 5023 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5024 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5025 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5026 PetscFunctionReturn(0); 5027 } 5028 5029 /*MC 5030 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5031 5032 Options Database Keys: 5033 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5034 5035 Level: beginner 5036 5037 .seealso: MatCreateAIJ() 5038 M*/ 5039 5040 #undef __FUNCT__ 5041 #define __FUNCT__ "MatCreate_MPIAIJ" 5042 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5043 { 5044 Mat_MPIAIJ *b; 5045 PetscErrorCode ierr; 5046 PetscMPIInt size; 5047 5048 PetscFunctionBegin; 5049 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5050 5051 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5052 B->data = (void*)b; 5053 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5054 B->assembled = PETSC_FALSE; 5055 B->insertmode = NOT_SET_VALUES; 5056 b->size = size; 5057 5058 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5059 5060 /* build cache for off array entries formed */ 5061 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5062 5063 b->donotstash = PETSC_FALSE; 5064 b->colmap = 0; 5065 b->garray = 0; 5066 b->roworiented = PETSC_TRUE; 5067 5068 /* stuff used for matrix vector multiply */ 5069 b->lvec = NULL; 5070 b->Mvctx = NULL; 5071 5072 /* stuff for MatGetRow() */ 5073 b->rowindices = 0; 5074 b->rowvalues = 0; 5075 b->getrowactive = PETSC_FALSE; 5076 5077 /* flexible pointer used in CUSP/CUSPARSE classes */ 5078 b->spptr = NULL; 5079 5080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5084 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5086 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5087 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5088 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5089 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5090 #if defined(PETSC_HAVE_ELEMENTAL) 5091 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5092 #endif 5093 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5094 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5095 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5096 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5097 PetscFunctionReturn(0); 5098 } 5099 5100 #undef __FUNCT__ 5101 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5102 /*@C 5103 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5104 and "off-diagonal" part of the matrix in CSR format. 5105 5106 Collective on MPI_Comm 5107 5108 Input Parameters: 5109 + comm - MPI communicator 5110 . m - number of local rows (Cannot be PETSC_DECIDE) 5111 . n - This value should be the same as the local size used in creating the 5112 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5113 calculated if N is given) For square matrices n is almost always m. 5114 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5115 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5116 . i - row indices for "diagonal" portion of matrix 5117 . j - column indices 5118 . a - matrix values 5119 . oi - row indices for "off-diagonal" portion of matrix 5120 . oj - column indices 5121 - oa - matrix values 5122 5123 Output Parameter: 5124 . mat - the matrix 5125 5126 Level: advanced 5127 5128 Notes: 5129 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5130 must free the arrays once the matrix has been destroyed and not before. 5131 5132 The i and j indices are 0 based 5133 5134 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5135 5136 This sets local rows and cannot be used to set off-processor values. 5137 5138 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5139 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5140 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5141 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5142 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5143 communication if it is known that only local entries will be set. 5144 5145 .keywords: matrix, aij, compressed row, sparse, parallel 5146 5147 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5148 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5149 @*/ 5150 PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5151 { 5152 PetscErrorCode ierr; 5153 Mat_MPIAIJ *maij; 5154 5155 PetscFunctionBegin; 5156 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5157 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5158 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5159 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5160 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5161 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5162 maij = (Mat_MPIAIJ*) (*mat)->data; 5163 5164 (*mat)->preallocated = PETSC_TRUE; 5165 5166 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5167 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5168 5169 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5170 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5171 5172 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5173 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5174 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5175 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5176 5177 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5178 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5179 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5180 PetscFunctionReturn(0); 5181 } 5182 5183 /* 5184 Special version for direct calls from Fortran 5185 */ 5186 #include <petsc/private/fortranimpl.h> 5187 5188 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5189 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5190 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5191 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5192 #endif 5193 5194 /* Change these macros so can be used in void function */ 5195 #undef CHKERRQ 5196 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5197 #undef SETERRQ2 5198 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5199 #undef SETERRQ3 5200 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5201 #undef SETERRQ 5202 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5203 5204 #undef __FUNCT__ 5205 #define __FUNCT__ "matsetvaluesmpiaij_" 5206 PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5207 { 5208 Mat mat = *mmat; 5209 PetscInt m = *mm, n = *mn; 5210 InsertMode addv = *maddv; 5211 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5212 PetscScalar value; 5213 PetscErrorCode ierr; 5214 5215 MatCheckPreallocated(mat,1); 5216 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5217 5218 #if defined(PETSC_USE_DEBUG) 5219 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5220 #endif 5221 { 5222 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5223 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5224 PetscBool roworiented = aij->roworiented; 5225 5226 /* Some Variables required in the macro */ 5227 Mat A = aij->A; 5228 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5229 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5230 MatScalar *aa = a->a; 5231 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5232 Mat B = aij->B; 5233 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5234 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5235 MatScalar *ba = b->a; 5236 5237 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5238 PetscInt nonew = a->nonew; 5239 MatScalar *ap1,*ap2; 5240 5241 PetscFunctionBegin; 5242 for (i=0; i<m; i++) { 5243 if (im[i] < 0) continue; 5244 #if defined(PETSC_USE_DEBUG) 5245 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5246 #endif 5247 if (im[i] >= rstart && im[i] < rend) { 5248 row = im[i] - rstart; 5249 lastcol1 = -1; 5250 rp1 = aj + ai[row]; 5251 ap1 = aa + ai[row]; 5252 rmax1 = aimax[row]; 5253 nrow1 = ailen[row]; 5254 low1 = 0; 5255 high1 = nrow1; 5256 lastcol2 = -1; 5257 rp2 = bj + bi[row]; 5258 ap2 = ba + bi[row]; 5259 rmax2 = bimax[row]; 5260 nrow2 = bilen[row]; 5261 low2 = 0; 5262 high2 = nrow2; 5263 5264 for (j=0; j<n; j++) { 5265 if (roworiented) value = v[i*n+j]; 5266 else value = v[i+j*m]; 5267 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5268 if (in[j] >= cstart && in[j] < cend) { 5269 col = in[j] - cstart; 5270 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5271 } else if (in[j] < 0) continue; 5272 #if defined(PETSC_USE_DEBUG) 5273 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 5274 #endif 5275 else { 5276 if (mat->was_assembled) { 5277 if (!aij->colmap) { 5278 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5279 } 5280 #if defined(PETSC_USE_CTABLE) 5281 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5282 col--; 5283 #else 5284 col = aij->colmap[in[j]] - 1; 5285 #endif 5286 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5287 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5288 col = in[j]; 5289 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5290 B = aij->B; 5291 b = (Mat_SeqAIJ*)B->data; 5292 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5293 rp2 = bj + bi[row]; 5294 ap2 = ba + bi[row]; 5295 rmax2 = bimax[row]; 5296 nrow2 = bilen[row]; 5297 low2 = 0; 5298 high2 = nrow2; 5299 bm = aij->B->rmap->n; 5300 ba = b->a; 5301 } 5302 } else col = in[j]; 5303 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5304 } 5305 } 5306 } else if (!aij->donotstash) { 5307 if (roworiented) { 5308 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5309 } else { 5310 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5311 } 5312 } 5313 } 5314 } 5315 PetscFunctionReturnVoid(); 5316 } 5317 5318